Power management system and control method

Abstract

The invention discloses a power management system and a control method. The system comprises a cloud server, a user terminal, a plurality of intelligent power strips and a wireless communication device, the cloud server and the user terminal are respectively connected with the plurality of intelligent power strips through the wireless communication device, the user terminal is connected with the cloud server, and the plurality of intelligent power strips are respectively connected with a plurality of load devices; the plurality of intelligent power strips are used for transmitting electric power data of the intelligent power strips to the cloud server and the user terminal through the wireless communication equipment, and the electric power data comprise one of voltage, current and temperature; the cloud server is used for determining early warning information according to the power data of the plurality of intelligent power strips and sending the early warning information to the user terminal; and the user terminal is used for sending an adjustment instruction to the plurality of intelligent power strips according to the early warning information, and the adjustment instruction is used for adjusting the plurality of intelligent power strips.

Description

Technical Field

[0001] This application relates to the technical field of power management, and more particularly, to a power management system and a control method. Background Art

[0002] With the digital and intelligent development of smart homes, office environments, and industrial facilities, power strips and sockets, as basic units of power management, have gradually evolved from traditional simple power connection devices to power control and monitoring devices with various intelligent functions. Especially in environments such as homes, offices, and large commercial buildings, multiple power strips and sockets are used to meet the power supply needs of various electrical devices. However, in the current related technologies, only the real-time control of a single power strip is concerned. For example, a user terminal or other devices are used to remotely control an intelligent power strip, but the process of managing the application process of a large number of power strips requires individual connection and control, resulting in low management efficiency. Summary of the Invention

[0003] Embodiments of this application provide a power management system and a control method to at least solve the technical problem of low management efficiency for a large number of intelligent power strips in the related technologies.

[0004] According to one aspect of the embodiments of this application, a power management system is provided, including: a cloud server, a user terminal, a plurality of intelligent power strips, and a wireless communication device. Among them, the cloud server and the user terminal are respectively connected to the plurality of intelligent power strips through the wireless communication device, the user terminal is connected to the cloud server, and the plurality of intelligent power strips are respectively connected to a plurality of load devices; the plurality of intelligent power strips are configured to transmit the power data of the intelligent power strips to the cloud server and the user terminal through the wireless communication device, where the power data includes one of the following: voltage, current, and temperature; the cloud server is configured to determine warning information based on the power data of the plurality of intelligent power strips and send the warning information to the user terminal; the user terminal is configured to send an adjustment instruction to the plurality of intelligent power strips according to the warning information, and the adjustment instruction is used to adjust the plurality of intelligent power strips.

[0005] Optionally, the intelligent power strip includes: a power management module, and the power management module is configured to divide the power data of each intelligent power strip into power data of multiple time windows, respectively determine the average power value of each time window, and determine that the intelligent socket is overloaded in the time window where the average power value is greater than the first threshold; the power management module is further configured to obtain the current peak value or power peak value of each time window, and determine that the intelligent socket is short-circuited in the time window where the current peak value is greater than the second threshold or the power peak value is greater than the third threshold.

[0006] Optionally, the power management module includes: a disconnection unit and an upload unit. The disconnection unit is configured to control the switch in the smart socket to disconnect when it is determined that the smart socket is overloaded or short-circuited. The upload unit is configured to generate fault data based on the power data corresponding to the smart socket and send the fault data to the cloud server after controlling the switch in the smart socket to disconnect.

[0007] Optionally, the cloud server is further configured to: associate the collected current data with the collection time to generate a power data sequence; use a pre-deployed prediction model to predict the power data sequence to obtain the power data within a preset period; obtain historical abnormal power data and compare the historical abnormal power data to obtain a first comparison result; and generate a first type of warning information according to the pre-determined mapping relationship between the abnormal type and the power data when the first comparison result indicates that the power data within the preset period is the same as the historical abnormal power data. The first type of warning information is used to indicate that a target type of power consumption abnormality will occur within the preset period.

[0008] Optionally, the cloud server is further configured to: traverse the power data of each time window in the power data sequence, compare the power data of each time window with a preset threshold to obtain a second comparison result; and generate a second type of warning information when the second comparison result indicates that the power data is higher than the preset threshold. The second type of warning information is used to indicate that the power data is higher than the preset threshold and the corresponding adjustment strategy.

[0009] Optionally, the user terminal is further configured to: receive a login request and display the collected power data and a target control when the login request passes the verification. When the target control is triggered, a control instruction is generated, and the control instruction is used to control the switches of the multiple smart sockets to disconnect.

[0010] Optionally, the smart socket is further configured to: receive the public key sent by the cloud server, encrypt the power data using the public key to obtain the encrypted power data, and send the encrypted power data to the cloud server, where the public key is in the certificate pre-deployed in the cloud server.

[0011] Optionally, the wireless communication device includes: a first communication module and a second communication module, where the number of smart sockets that the first communication module can access is less than that of the second communication module.

[0012] Optionally, the cloud server is further configured to: encrypt the historical abnormal power data and the collected power data and store them in the storage module of the cloud server.

[0013] According to another aspect of the embodiments of the present application, a control method for a power management system is further provided, including: receiving power data of a plurality of smart plugs, where the power data includes one of the following: voltage, current, and temperature; determining warning information according to the power data of the plurality of smart plugs, and sending the warning information to the user terminal, where the warning information is used to determine an adjustment instruction, and the adjustment instruction is used to adjust the plurality of smart plugs.

[0014] According to still another aspect of the embodiments of the present application, a computer device is further provided, including: a memory and a processor, where the memory is used to store program instructions; the processor, connected to the memory, is used to execute the above control method of the power management system.

[0015] According to yet another aspect of the embodiments of the present application, a non-volatile storage medium is further provided, where the non-volatile storage medium includes a stored computer program, and the device where the non-volatile storage medium is located executes the above control method of the power management system by running the computer program.

[0016] According to yet another aspect of the embodiments of the present application, a computer program product is further provided, including computer instructions, and when the computer instructions are executed by a processor, the above control method of the power management system is implemented.

[0017] In the embodiments of the present application, a cloud server, a user terminal, a plurality of smart plugs, and a wireless communication device are adopted. The cloud server and the user terminal are respectively connected to the plurality of smart plugs through the wireless communication device, the user terminal is connected to the cloud server, and the plurality of smart plugs are respectively connected to a plurality of load devices; the plurality of smart plugs are used to transmit the power data of the smart plugs to the cloud server and the user terminal through the wireless communication device, where the power data includes one of the following: voltage, current, and temperature; the cloud server is used to determine warning information according to the power data of the plurality of smart plugs and send the warning information to the user terminal; the user terminal is used to send an adjustment instruction to the plurality of smart plugs according to the warning information, and the adjustment instruction is used to adjust the plurality of smart plugs, thereby achieving the purpose of accurately managing each smart plug in the plurality of smart plugs according to the analysis result of the cloud server, thereby realizing the technical effect of improving the management efficiency of a large number of smart plugs, and further solving the technical problem of low management efficiency of a large number of smart plugs in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings described herein are used to provide a further understanding of the present application and form a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings:

[0019] Figure 1 is a hardware structure block diagram of a power management system according to an embodiment of the present application;

[0020] Figure 2 is a flowchart of a control method of a power management system according to an embodiment of the present application. Detailed implementation manners

[0021] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above accompanying drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence. It should be understood that such data used in appropriate cases can be interchanged so that the embodiments of the present application described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0023] The information collected in the embodiments of the present application is information and data authorized by the user or fully authorized by all parties. Moreover, the processing of the relevant data, such as collection, storage, use, processing, transmission, provision, disclosure, and application, complies with the relevant laws, regulations, and standards of the relevant regions, takes necessary confidentiality measures, does not violate public order and good customs, and provides corresponding operation entrances for the user to choose to authorize or reject the results of automated decision-making. If the user chooses to reject, the expert decision-making process will be entered.

[0024] An embodiment of a scheduling method for a drone communication system is provided in this application. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0025] Figure 1 It is a schematic structural diagram of a power management system according to an embodiment of the present application. As Figure 1 shown, the system includes:

[0026] A cloud server 10, a user terminal 20, a plurality of smart power strips 30, and a wireless communication device 40. Among them, the cloud server 10 and the user terminal 20 are respectively connected to the plurality of smart power strips 30 through the wireless communication device 40. The user terminal 20 is connected to the cloud server 10. The plurality of smart power strips 30 are respectively connected to a plurality of load devices (not shown in the figure); the plurality of smart power strips 30 are used to transmit the power data of the smart power strips 30 to the cloud server 10 and the user terminal 20 through the wireless communication device 40. Among them, the power data includes one of the following: voltage, current, and temperature; the cloud server 10 is used to determine warning information according to the power data of the plurality of smart power strips 30 and send the warning information to the user terminal 20; the user terminal 20 is used to send an adjustment instruction to the plurality of smart power strips 30 according to the warning information, and the adjustment instruction is used to adjust the plurality of smart power strips 30.

[0027] It should be noted that the smart power strip 30 can also be a smart socket.

[0028] Through the above system, a plurality of smart power strips 30 and socket devices are integrated into a unified platform to realize centralized monitoring, intelligent control, and fault warning of multiple devices.

[0029] In some embodiments of the present application, the smart power strip 30 includes: a power management module. The power management module is used to divide the power data of each smart power strip 30 into power data of multiple time windows, respectively determine the average power value of each time window, and determine that the smart socket is overloaded in the time window where the average power value is greater than the first threshold; the power management module is further used to obtain the current peak value or power peak value of each time window, and determine that the smart socket is short-circuited in the time window where the current peak value is greater than the second threshold or the power peak value is greater than the third threshold.

[0030] Among them, the power management module further includes: a disconnection unit and an upload unit. The disconnection unit is configured to control the switch in the intelligent socket strip 30 to disconnect when it is determined that the intelligent socket is overloaded or short-circuited. The upload unit is configured to generate fault data based on the power data corresponding to the intelligent socket after controlling the switch in the intelligent socket strip 30 to disconnect, and send the fault data to the cloud server 10.

[0031] It should be noted that the above control logic can be implemented by pre-written embedded software.

[0032] Taking the i-th intelligent socket strip 30 as K i as an example, the multiple time windows corresponding to K i are respectively t1, t2,... t n , where n represents the number of time windows. Calculate the average power value within each time window corresponding to K i as P1, P2,... P n . Select the time window corresponding to the average power value greater than the first threshold from the n average power values as the first target time window, and determine that K i is overloaded in the first target time window.

[0033] It can be understood that the method for determining the second target time window based on the current peak or power peak of each time window corresponding to K i is similar to the method for determining the first target time window, which will not be elaborated here. Among them, in the second target time window, the current peak of K i is greater than the second threshold or the power peak of K i is greater than the third threshold.

[0034] It should also be noted that the length of the time window can be set according to actual needs, for example: 1 minute, 5 minutes, and 1 hour.

[0035] In the embodiments of the present application, the power management module uses algorithms such as power analysis based on time windows, voltage and current anomaly detection (overload, short circuit, etc.), temperature monitoring, and fault warning to perform real-time analysis on the sensor data obtained through the embedded system, calculate power consumption, and judge the load situation, etc.

[0036] In an actual application scenario, the cloud server 10 can store the collected power data and the device information of multiple smart plugs 30 in the storage unit (database) of the cloud server 10, and analyze the collected power data to determine the power consumption pattern and the abnormal behavior of the smart plugs 30. Specifically, the cloud server 10 is further configured to: associate the collected current data with the collection time to generate a power data sequence; use a pre-deployed prediction model to predict the power data sequence to obtain the power data within a preset period; obtain historical abnormal power data, and compare the historical abnormal power data to obtain a first comparison result; in the case where the first comparison result indicates that the power data within the preset period is the same as the historical abnormal power data, generate a first type of warning information according to the mapping relationship between the pre-determined abnormal type and the power data, and the first type of warning information is used to indicate that a target type of power consumption abnormality will occur within the preset period.

[0037] Specifically, the current sensor built into each smart plug 30 collects the current data of the connected electrical appliance in real time, associates the data with the collection time (for example, a time stamp accurate to the second), and uploads it to the cloud server 10. The cloud server 10 receives and processes these data, arranges the current data of each plug in chronological order, and generates a power data sequence.

[0038] A prediction model trained based on historical data is pre-deployed on the cloud server 10. This model can identify the power consumption patterns in the deployment areas of multiple smart plugs 30 and predict the power data within a certain future period. Using the historical power data sequence as training data, the model learns the time series characteristics of the power data by analyzing factors such as power, seasonal changes, and device usage patterns in the deployment area. For example, the prediction model may find that 4 pm to 6 pm every day is the peak electricity consumption period. And based on the current real-time data sequence, the prediction model calculates the power data prediction for a future period of time. For example, it predicts the power consumption at each time point within the next 24 hours. Generate a power usage plan to avoid overload during peak periods.

[0039] The process of abnormal data comparison and warning generation is as follows: The cloud server 10 obtains historical abnormal power data from the database, including the current data sequences of known events such as overload, short circuit, and voltage fluctuation. Compare and analyze the power data within the preset period with the historical abnormal power data to check for similar patterns. For example, if there is a sudden large increase in current in the predicted data, this may be similar to the historical data of an overload event.

[0040] If the predicted data highly coincides with the historical abnormal data, that is, the first comparison result indicates an abnormal pattern, the cloud server 10 will generate a first type of warning information according to the mapping relationship between the preset abnormal type and the power data. For example: match the power data pattern with the abnormal type (such as overload, short circuit) to generate the corresponding warning information.

[0041] Among them, the first type of warning information will include a detailed abnormal description, the predicted time point of occurrence, and possible solutions or preventive measures. For example, the warning information may indicate that the smart socket 30 may be overloaded between 4 pm and 6 pm tomorrow, and it is recommended that the user reduce the use of electrical appliances or switch to other sockets during this period.

[0042] In another alternative manner, the cloud server 10 can also perform real-time judgment on the power data. Specifically, the cloud server 10 is further configured to: traverse the power data of each time window in the power data sequence, compare the power data of each time window with a preset threshold to obtain a second comparison result; in the case where the second comparison result indicates that the power data is higher than the preset threshold, generate a second type of warning information, and the second type of warning information is used to indicate that the power data is higher than the preset threshold and the corresponding adjustment strategy.

[0043] For example: the average power value, the peak power value, and the peak current value of each time window respectively correspond to different preset thresholds. The preset threshold corresponding to the average power value of each time window is the first preset threshold, the preset threshold corresponding to the peak current value is the second preset threshold, and the preset threshold corresponding to the peak power value is the third preset threshold. It can be understood that the first preset threshold is less than the first threshold, the second preset threshold is less than the second threshold, and the third preset threshold is less than the third threshold.

[0044] Specifically, the cloud server 10 makes real-time judgments on power data. By comparing the data in each time window of the power data sequence with a preset threshold, it generates the second type of warning information. The specific implementation steps are as follows: Step 1: Define the time window and threshold. First, the cloud server 10 needs to define the size of the time window, which is usually determined according to the fluctuation frequency of power data and monitoring requirements. For example, the time window can be set to 1 minute, 5 minutes, or longer. Then, set preset thresholds for each indicator (average power, power peak, current peak). For example, for the average power, set the first preset threshold to 1000 watts, which is lower than the first threshold (e.g., 1200 watts) that the system may set to give an early warning of potential overload risks; for the current peak, set the second preset threshold to 15 amperes, lower than the second threshold (e.g., 18 amperes) to give an early warning of potential short-circuit risks; for the power peak, set the third preset threshold to 1500 watts, lower than the third threshold (e.g., 1800 watts) to give an early warning of potential short-circuit risks. Step 2: Data traversal and threshold comparison: The cloud server 10 traverses each time window in the power data sequence and analyzes the data within each window. For example, for each 1-minute time window, calculate the average power, power peak, and current peak within the window, and then compare these values with the preset thresholds. Step 3: Generate the second comparison result: If it is found during the traversal that the data in any time window exceeds the preset threshold, the cloud server 10 will generate a second comparison result indicating that there is power data exceeding the threshold within that time window. For example, assume that the average power within a certain time window is 1100 watts, higher than the first preset threshold of 1000 watts; the current peak is 16 amperes, higher than the second preset threshold of 15 amperes; and the power peak is 1450 watts, lower than the third preset threshold of 1500 watts. In this case, the cloud server 10 will generate two second comparison results of exceeding the threshold: the average power exceeds the first preset threshold and the current peak exceeds the second preset threshold. Step 4: Generate and send the second type of warning information: Once it is found that the power data exceeds the preset threshold, the cloud server 10 will generate the second type of warning information according to the corresponding time window. The warning information includes the specific data exceeding the threshold, the start and end times of the time window, and the recommended adjustment strategy. For example, warning information 1: The average power exceeds the first preset threshold. It is recommended to reduce the use of high-power-consuming appliances or transfer some appliances to other smart sockets 30 to avoid overload. Warning information 2: The current peak exceeds the second preset threshold. It is recommended to turn off some appliances that are not in use temporarily or adjust the usage time of the appliances to reduce the instantaneous current peak.

[0045] In an actual application scenario, the user terminal 20 is further configured to: receive a login request, and when the login request passes verification, display the collected power data and target controls, where, when the target controls are triggered, generate a control instruction for controlling the switches of the multiple smart sockets 30 to disconnect.

[0046] It should be noted that the target controls can be buttons on the screen of the user terminal 20 that can be triggered.

[0047] Specifically, the user controls and monitors the smart socket 30 through a mobile phone APP, where the control instructions include: device management, real-time monitoring, remote control, fault warning, etc.

[0048] In addition, a central management platform can also be provided to facilitate users to manage devices on the web side. The front end uses vue.js to develop an interactive user interface, and the back end uses java to process user requests, send control instructions to devices, and receive data.

[0049] Since the smart socket 30 involves household electricity information and device control, the security of the communication process must be ensured. The SSL / TLS encryption method is used to secure data transmission, especially for the communication between the cloud and the device. The AES encryption method is used to encrypt the stored data, such as device information, user data, etc. Through authentication and authorization: ensure that users can only access their own devices and prevent unauthorized operations. Use JWT for user authentication. Two-factor authentication (2FA) enhances system security.

[0050] The specific process of communication encryption is as follows: The smart socket 30 is further configured to: receive the public key sent by the cloud server 10, encrypt the power data using the public key to obtain the encrypted power data, and send the encrypted power data to the cloud server 10, where the public key is in the certificate pre-deployed in the cloud server 10.

[0051] In some embodiments of the present application, the wireless communication device 40 includes: a first communication module and a second communication module, where the number of smart sockets 30 that the first communication module can access is less than that of the second communication module.

[0052] For example: The first communication module is a router (wifi module), and the second communication module is a Zigbee module.

[0053] The cloud server 10 encrypts the historical abnormal power data and the collected power data and stores them in the storage module of the cloud service.

[0054] To better understand the power management system proposed in this application, the following separately describes the specific application steps of power management for the scenarios applicable to the first communication module and the second communication module.

[0055] Take a small-scale home intelligent socket management system (Wi-Fi solution). Small-scale means that the number of intelligent sockets is less than a preset number, for example: 50.

[0056] Regarding the power management requirements of multiple intelligent sockets in a home environment, users hope to achieve remote control and status monitoring of the sockets through a smartphone application. The system should have basic fault detection and early warning functions and be able to record power data. Wireless communication technology: Select the Wi-Fi protocol. Each intelligent socket is connected to the home router via Wi-Fi, facilitating communication with the cloud platform and the mobile APP. Hardware design: Each socket includes an integrated current, voltage, and temperature sensor module for real-time monitoring of the socket's operating status. The control chip uses ESP32, which has a built-in Wi-Fi module, can communicate with the cloud, and has sufficient computing power for basic fault detection (such as overload and short circuit). Embedded software: Use C / C++ to develop embedded control logic, including functions such as current and voltage acquisition, overload judgment, temperature monitoring, and data uploading to the cloud server. Calculate power consumption through the time window analysis method and process sensor data in real time. If an overload or short circuit occurs, immediately cut off the power and upload the fault data to the cloud server.

[0057] Cloud server: The cloud server stores the status data, historical power data, and fault logs of the device. Manages device and data interaction. Analyzes the power consumption pattern in real time and detects abnormal behaviors (such as abnormal power fluctuations, device failures, etc.).

[0058] Application terminal: Supports users to view the real-time status of each intelligent socket, including information such as power, voltage, temperature, and power consumption. Provides a remote control function. Users can control the switch of the socket through the APP, view historical data, set power consumption reminders, and fault warnings. The APP can timely push notifications to remind users according to the warning information sent by the cloud server, avoiding device failures or safety hazards.

[0059] Data encryption and security: Use the SSL / TLS encryption protocol to protect communication security and ensure the security of data transmission between the cloud and the device. The stored user data and device information are protected using AES encryption. Implement JWT user authentication and two-factor authentication (2FA) to enhance the security of the system and prevent unauthorized access.

[0060] Fault Detection and Intelligent Scheduling: The system monitors data such as voltage, current, and temperature in real time, uses time series analysis to identify abnormal fluctuations, automatically determines whether there are equipment failures, and pushes fault warnings. Based on the load conditions of the equipment, it dynamically adjusts the switch states of the equipment to avoid overload and optimize power consumption efficiency.

[0061] The specific implementation steps are as follows: Install smart sockets at various power interfaces in the home and connect them to the router; embed the ESP32 module in the smart sockets and configure sensors to collect power data; write control programs to achieve data collection and fault detection; build a cloud platform for data storage and analysis; develop and release an Android application so that users can remotely monitor and control the sockets through their mobile phones; configure encryption transmission and authentication mechanisms to ensure the security of the system.

[0062] Users can remotely control and monitor smart sockets through the APP, view real-time power consumption, temperature, and power conditions. The system can detect faults in real time and give early warnings in a timely manner to avoid safety accidents caused by electrical overload or other faults. The cloud server can analyze users' power data, provide energy-saving suggestions, and optimize household power consumption.

[0063] For the intelligent power management system (Zigbee solution) in large commercial office buildings, on a large scale, it includes: the number of smart sockets is greater than the preset number, for example: 50.

[0064] For the centralized management requirements of multiple intelligent power strips and sockets in large commercial office buildings, property management parties hope to uniformly monitor hundreds of sockets in the building, provide fault warnings, conduct energy-saving analysis, and perform load scheduling to ensure the safe and efficient operation of equipment. Wireless communication technology: The Zigbee protocol is selected. Due to the large number of devices in the office building, the low-power and low-bandwidth characteristics of Zigbee make it an ideal choice. Each intelligent socket and power strip is connected to a centralized Zigbee gateway via Zigbee, and then connected to the cloud platform through the gateway. Hardware design: Each power strip and socket is equipped with current, voltage, and temperature sensors, and integrates a Zigbee module (such as Xbee) for data communication. The gateway device is connected to a local server or cloud server via wired or Wi-Fi. Embedded software: Use a computer language to write the embedded control logic of the socket, collect sensor data, and communicate with the gateway. Regularly send the collected data to the cloud server for real-time analysis of data such as power consumption, load conditions, and temperature. Implement fault detection for overload, short circuit, over-temperature, etc., and automatically cut off the power to prevent equipment damage. Cloud server: Use a cloud platform to manage devices, store device status, historical power data, fault logs, etc. Use the stream data processing platform in the cloud platform to analyze the power consumption patterns of devices in real time, detect abnormal behaviors of devices, and provide fault warnings. Web application and backend management platform: Provide a Web management platform where property management personnel can view the status, power consumption, fault logs, etc. of intelligent sockets throughout the building. Build a front-end and back-end architecture to support remote control, fault detection, status monitoring, and historical data query of devices. Security and privacy protection: Use TLS (an encryption method) to encrypt and protect the data transmission between Zigbee and the gateway, and between the gateway and the cloud platform. Perform AES encryption storage on all device and user data to ensure user privacy and device information security. Use JWT (a permission verification method) for user authentication to ensure that only authorized personnel can access the management platform, and use two-factor authentication to enhance the security of the system. Load scheduling and intelligent scheduling: Based on electricity demand and device status, the system can dynamically adjust the on / off of devices, avoid overload, and optimize energy distribution. Use genetic algorithms or dynamic programming algorithms to achieve optimal load scheduling and reasonably allocate power resources.

[0065] The specific implementation steps are as follows: Install intelligent sockets and power strips, and configure the Zigbee communication module to ensure that all devices can access the Zigbee network; Configure and install the gateway device and establish a connection with the cloud server; Write embedded software to ensure that the device can collect data such as current, voltage, and temperature and send it to the cloud; Develop and deploy the Web management platform for property management personnel to monitor and control devices in real time; Configure the cloud server for data storage, processing, and analysis to ensure that the system can detect faults in real time and optimize load scheduling.

[0066] Property managers can monitor the status of all smart sockets in the building in real time through the Web platform, view historical electricity consumption data, detect power anomalies, and handle faults in a timely manner. The system can automatically give early warnings and cut off faulty equipment to avoid electrical fires or equipment damage. Through intelligent scheduling and load optimization, the system can effectively reduce power waste and improve energy efficiency.

[0067] In the embodiments of this application, the provided power management system intelligently integrates and manages multiple smart power strips and socket devices, solving the limitations of single-device management in the prior art and having the following advantages: Centralized monitoring and control: By integrating multiple smart power strips and socket devices into a unified platform, users can centrally manage all devices, whether it is a small-scale deployment in a home environment or a large-scale deployment in a large commercial environment. Whether through the mobile phone APP or the Web management platform, the system can provide real-time monitoring and remote control of the devices, greatly improving the management efficiency of power equipment. The system can dynamically adjust the operating status of the devices according to the real-time power demand, avoid overload and optimize the power usage. This is achieved through optimization algorithms (such as genetic algorithms and dynamic programming) for load balancing to ensure that each device can operate efficiently under an appropriate load and avoid energy waste. Flexible selection of Wi-Fi and Zigbee: According to different application scenarios, the system can flexibly select the communication protocol. For home or small office environments, the Wi-Fi protocol is simple and easy to use, and users can directly connect to the home router; while for large-scale commercial or office building environments, Zigbee has the advantages of low power consumption and long-term stable operation, can support the simultaneous connection of more devices, and can effectively reduce the network burden when covering a large area. Multi-dimensional fault detection: The system deeply analyzes the working status of the devices by using time series analysis and machine learning algorithms through real-time monitoring of data such as current, voltage, and temperature, timely discovers abnormal fluctuations, and accurately judges fault situations such as overload, short circuit, and overheating. Through the application of intelligent algorithms, the system can identify potential risks in advance and push warning notifications to users in a timely manner to prevent equipment damage and safety hazards. Automatic response: Once a fault is detected, the system can immediately cut off the power automatically, reduce the risk of equipment damage, and trigger the fault alarm mechanism to ensure that users can take remedial measures in the shortest possible time. Through the storage and computing capabilities of the cloud platform, the system can gather a large amount of device data for analysis, mine power consumption patterns and abnormal behaviors. Using big data tools, the system can process and analyze data in real time, provide users with energy-saving optimization suggestions, power consumption trend predictions, and equipment maintenance suggestions, further improving the management efficiency and energy utilization rate. Device status historical tracking: The system can not only perform real-time monitoring, but also store historical power data and fault logs to help users track the long-term operating status of the devices, facilitate predicting the service life of the devices and performing regular maintenance. All data transmissions between the smart power strip and the cloud platform use the SSL / TLS encryption protocol to ensure the security of user data. At the same time, the device information, user data, etc. stored in the cloud are also protected using AES encryption to avoid data leakage. The system performs identity verification through JWT to ensure that only authorized users can access the device management platform. Combined with two-factor authentication (2FA), the security of the system is further enhanced, effectively preventing unauthorized access and operations.The system has high-precision current, voltage, and power monitoring capabilities, can reflect the power consumption of devices in real time, and conduct accurate power consumption analysis. This enables users to understand the power consumption of each socket and power strip, and promptly identify high-power-consuming devices. By adopting optimized communication protocols and embedded control systems, it ensures the real-time collection of device status data and the rapid response of the cloud platform, reduces communication latency, and ensures that users can obtain real-time system status and warning information. The hardware and software architecture of the system adopts a modular design, making it easier to add devices and upgrade the system. Whether adding new smart socket devices or expanding to new management platform functions, it can be seamlessly connected through software upgrades and hardware additions. It not only supports remote control via mobile APP (Android / iOS), but also provides a web-based management platform, allowing users to conveniently access and operate the system on different devices, enhancing the usability and flexibility of the system. Under different power demands, the system can intelligently adjust the operating status of devices, reasonably allocate power resources, avoid ineffective energy waste, reduce the carbon footprint, and promote the realization of green office and environmental protection goals.

[0068] Figure 2 A control method for a power management system according to an embodiment of the present application, the method includes:

[0069] Step S202, receiving power data of multiple smart power strips, where the power data includes one of the following: voltage, current, and temperature;

[0070] Step S204, determining warning information based on the power data of the multiple smart power strips, and sending the warning information to the user terminal, where the warning information is used to determine an adjustment instruction, and the adjustment instruction is used to adjust the multiple smart power strips.

[0071] It should be noted that Figure 2 The control method of the power management system shown is used to execute Figure 1 The power management system shown, so the relevant explanations in the control method of the above power management system also apply to this power management system, and will not be elaborated here.

[0072] An embodiment of the present application also provides a computer device, including: a memory and a processor, where the memory is used to store program instructions; the processor, connected to the memory, is used to execute the control method of the above power management system.

[0073] An embodiment of the present application also provides a non-volatile storage medium, which includes a stored computer program, where the device where the non-volatile storage medium is located executes the control method of the above power management system by running the computer program.

[0074] The embodiment of the present application also provides a computer program product, including computer instructions, which implement the steps of the control method of the power management system in the present application when executed by a processor.

[0075] The serial numbers of the embodiments of the present application above are only for description and do not represent the advantages or disadvantages of the embodiments.

[0076] In the above embodiments of the present application, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0077] In the several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the units or modules can be in electrical or other forms.

[0078] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] In addition, the functional units in the respective embodiments of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0080] When 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 this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0081] The above are only the preferred embodiments of this application. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. A power management system, characterized in that, Including: A cloud server, user terminals, multiple smart socket strips, and a wireless communication device. Among them, the cloud server and the user terminals are respectively connected to the multiple smart socket strips through the wireless communication device. The user terminals are connected to the cloud server, and the multiple smart socket strips are respectively connected to multiple load devices; The multiple smart socket strips are used to transmit the power data of the smart socket strips to the cloud server and the user terminals through the wireless communication device. Among them, the power data includes one of the following: voltage, current, and temperature; The cloud server is used to determine warning information based on the power data of the multiple smart socket strips and send the warning information to the user terminals; The user terminals are used to send adjustment instructions to the multiple smart socket strips according to the warning information. The adjustment instructions are used to adjust the multiple smart socket strips.

2. The system according to claim 1, wherein The smart socket strip includes: A power management module. The power management module is used to divide the power data of each smart socket strip into power data of multiple time windows, respectively determine the average power value of each time window, and determine that the smart socket is overloaded in the time window when the average power value is greater than the first threshold; The power management module is further used to obtain the current peak value or power peak value of each time window, and determine that the smart socket is short-circuited in the time window when the current peak value is greater than the second threshold or the power peak value is greater than the third threshold.

3. The system according to claim 2, wherein The power management module includes: A disconnection unit and an upload unit. Among them, The disconnection unit is used to control the switch in the smart socket strip to disconnect when it is determined that the smart socket is overloaded or short-circuited; The upload unit is used to generate fault data according to the power data corresponding to the smart socket and send the fault data to the cloud server after controlling the switch in the smart socket strip to disconnect.

4. The system according to claim 1, characterized in that The cloud server is further used to: Associate the collected current data with the collection time to generate a power data sequence; Use a pre-deployed prediction model to predict the power data sequence to obtain the power data within a preset period; Obtain historical abnormal power data and compare the historical abnormal power data to obtain a first comparison result; In the case where the first comparison result indicates that the power data within the preset period is the same as the historical abnormal power data, generate a first type of warning information according to the pre-determined mapping relationship between the abnormal type and the power data. The first type of warning information is used to indicate that an abnormal power consumption of the target type will occur within the preset period.

5. The system according to claim 4, characterized in that, The cloud server is further used to: Traverse the power data of each time window in the power data sequence, compare the power data of each time window with a preset threshold to obtain a second comparison result; In the case where the second comparison result indicates that the power data is higher than the preset threshold, generate a second type of warning information. The second type of warning information is used to indicate that the power data is higher than the preset threshold and the corresponding adjustment strategy.

6. The system according to claim 5, wherein The user terminal is further used to: Receive a login request, and when the login request passes verification, display the collected power data and target controls. Among them, when the target control is triggered, a control instruction is generated, and the control instruction is used to control the switches of the multiple smart plugs to disconnect.

7. The system according to claim 1, wherein The smart plug is further used for: Receive the public key sent by the cloud server, encrypt the power data using the public key to obtain the encrypted power data, and send the encrypted power data to the cloud server, where the public key is in the certificate pre-deployed in the cloud server.

8. The system according to claim 1, wherein The wireless communication device includes: A first communication module and a second communication module, where the number of smart plugs that the first communication module can access is less than that of the second communication module.

9. The system according to claim 4, characterized in that, The cloud server is further used for: After encrypting the historical abnormal power data and the collected power data, store them in the storage module of the cloud server.

10. A control method for a power management system, characterized in that, Include: Receive the power data of multiple smart plugs, where the power data includes one of the following: voltage, current, and temperature; Determine early warning information based on the power data of the multiple smart plugs, and send the early warning information to the user terminal, where the early warning information is used to determine an adjustment instruction, and the adjustment instruction is used to adjust the multiple smart plugs.

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