Power optimization system and method based on Internet of Things

Abstract

The invention relates to the technical field of power equipment operation and maintenance, and provides a power optimization system and method based on the Internet of Things, and the system achieves the precise prediction and optimization of the operation state of power equipment through the comprehensive application of the Internet of Things technology, data analysis and a machine learning algorithm, and comprises a plurality of modules. The power equipment is comprehensively monitored and optimized through cooperative work, the operation of the power equipment is effectively predicted and early warned in advance by dynamically dividing the control area, periodically updating the equipment data and optimizing the power system model through big data, the operation efficiency and reliability of the power system are remarkably improved, the operation and maintenance cost is reduced, and the operation efficiency of the power system is improved. And powerful support is provided for intelligent management and optimization of a power system.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment operation and maintenance, and in particular to a power optimization system and method based on the Internet of Things. Background Art

[0002] The power system based on the Internet of Things refers to the use of Internet of Things technology to monitor, manage and optimize the operation of the power system. The Internet of Things technology can connect various devices and sensors to improve the efficiency and reliability of the power system through real-time data collection and analysis. In the power system based on the Internet of Things, various intelligent devices and sensors are deployed at various key nodes of the power grid, such as power stations, substations, transmission lines and distribution facilities. These devices and sensors can monitor the status of the power grid in real time, such as voltage, current, power factor, etc., and transmit these data to the central control system through wireless or wired networks. The central control system can analyze these data to achieve real-time monitoring and prediction of the power system. If an abnormal situation is found, the system can respond quickly, such as adjusting the output power of the generator or switching the backup power supply to ensure the stable operation of the power system.

[0003] The introduction of IoT technology in the power system faces the challenge of equipment compatibility. Due to the large number of equipment in power plants, the models of various equipment and the different usage conditions of the equipment, the number of equipment in the IoT and the communication status of the equipment are in dynamic change, resulting in inaccurate prediction of the operating status of the IoT power equipment by the system. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides an Internet of Things-based power optimization system and method to solve the problem that the system cannot accurately predict the operating status of power equipment in the Internet of Things due to the large number of equipment in the power plant, the different models of various equipment and the different usage conditions of the equipment, and the dynamic changes in the number of equipment and the communication status of the equipment in the Internet of Things.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0006] In a first aspect, an Internet of Things-based power optimization system includes: a control device end and a background control end, a user terminal, and a device end, wherein the control device end establishes a communication connection with the background control end, the user terminal, and the device end, and the control device end processes data transmitted by the user terminal and the device end to obtain a prediction result of the operating state of the device in the Internet of Things, and the control device end sends the prediction result of the operating state of the device in the Internet of Things to the background control end, the user terminal, and the device end, wherein the control device end includes:

[0007] A data acquisition module is used to acquire power equipment operation data, which includes equipment location data, equipment status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormality and failure, and equipment operation record data;

[0008] A control partition establishment module is used to divide the area where the equipment is located into control areas according to the equipment location data to obtain control areas. The control areas include a control area main node, a control sub-area and a control device node. The control area main node establishes a communication connection with the control device node. Each control sub-area is configured with a control device node. The control device node is used to communicate with the equipment in the control device sub-area.

[0009] The power equipment update module is used for the control device to send the equipment data update instruction to the control sub-area according to the preset time period. After the control device node of the control sub-area receives the equipment data update instruction, it sends a status inspection command to the equipment in the control sub-area to which it belongs. After the equipment in the control sub-area feeds back the equipment operation data to the control device node, the control device node updates the equipment data in the control sub-area and sends the updated equipment data to the control area master node;

[0010] The power equipment monitoring module is used to control the regional master node to generate a new equipment inspection and monitoring list according to the updated equipment data, monitor the equipment in real time according to the new equipment inspection and monitoring list, obtain the real-time monitoring data of the equipment, compare the new equipment inspection and monitoring list with the equipment inspection and monitoring list before the update, and obtain the list clearing equipment information;

[0011] The power system optimization module is used to retrieve the list to clear the device information history and the real-time monitoring data of the equipment to optimize the preset power system optimization, obtain the optimized power system optimization model, substitute the real-time monitoring data of the equipment into the optimized power system optimization model, and obtain the operating status prediction results of the equipment in the Internet of Things.

[0012] Furthermore, the present invention provides the power optimization system based on the Internet of Things, wherein the data acquisition module is further used for:

[0013] Send communication information to each device on the device side, obtain communication information fed back by each device on the device side, extract device features from the communication information fed back by each device on the device side, obtain a list of devices corresponding to the feedback information, compare each device on the device side with the list of devices corresponding to the feedback information, and obtain devices with feedback information and devices without feedback information;

[0014] Perform communication protocol matching on the device without feedback information. If the matching is successful, configure the successfully matched communication protocol on the device without feedback information.

[0015] According to the preset time interval or trigger condition, a data request is sent to the device side, and the required data type is specified in the data request sent to the device side. The required data type includes device location data, device status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormal failure and equipment operation record data.

[0016] Furthermore, the present invention provides the power optimization system based on the Internet of Things, wherein the control partition establishment module is further used for:

[0017] Analyze the equipment location data to determine the spatial distribution and relative position relationship of the equipment. According to the equipment location information and the actual needs of the power system, formulate the division rules of the control area. The division rules of the control area include geographical location, equipment type, and load conditions;

[0018] According to the control area division rules, the equipment is divided into different control areas. Each control area should contain equipment corresponding to the geographical location;

[0019] Set up the control area master node and control device node:

[0020] In each control area, a control area master node is set up to correspond to the overall control and coordination within the control area;

[0021] A control device node is configured for each control sub-area for communicating with and controlling the equipment in the corresponding control sub-area.

[0022] Furthermore, the present invention provides the power optimization system based on the Internet of Things, wherein the power equipment updating module is further used for:

[0023] Setting a preset time period, and a frequency of sending device data update instructions to the control sub-area according to the preset time period;

[0024] At each preset time point, a device data update instruction is sent to the control device node of each control sub-area, where the device data update instruction includes the control device node performing a status inspection on the device in the control sub-area to which it belongs;

[0025] After sending the device data update instruction, wait for the status inspection feedback of the equipment in the control sub-area. After receiving the instruction, the control device node will send a status inspection command to the equipment in the area.

[0026] After receiving the status inspection command, the device performs a self-inspection and feeds back the device operation data to the control device node;

[0027] After receiving the operating data of all devices in the area to which it belongs, the control device node integrates and updates these data. The control device node uploads the updated device data to the control area master node, which then transmits it to the control area master node;

[0028] If any equipment abnormality or failure is found during the status inspection, the control device node will issue an abnormal situation warning.

[0029] Furthermore, the present invention provides the power optimization system based on the Internet of Things, wherein the power system optimization module is further used for:

[0030] Retrieve the information history of the device that has been cleared from the list. The information history of the device that has been cleared from the list includes the operating data and fault records of the device that has been cleared or replaced;

[0031] Integrate the historical data of the cleared equipment with the real-time monitoring data of the current equipment, analyze the integrated data, and identify the equipment's operating trends, failure modes, and performance bottlenecks;

[0032] Based on the preset power system optimization objectives and constraints, use machine learning algorithms to build or update power system optimization models;

[0033] The historical data of the cleared equipment and the real-time monitoring data of the current equipment are integrated as input to train and optimize the model. The optimized model is verified using the historical data. If the verification is successful, the optimized power system optimization model is obtained.

[0034] Substitute the real-time monitoring data of the equipment into the optimized power system optimization model;

[0035] The optimized power system optimization model is used to calculate the operating status prediction results of the equipment in the Internet of Things, which include the probability of equipment failure, performance degradation trend and energy consumption prediction.

[0036] In a second aspect, a power optimization method based on the Internet of Things is applied to the power optimization system based on the Internet of Things, comprising:

[0037] Step S101, obtaining power equipment operation data, the power equipment operation data including equipment location data, equipment status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormality and failure, and equipment operation record data;

[0038] Step S102: According to the device location data, the area where the device is located is divided into control areas to obtain control areas, where the control areas include a control area master node, a control sub-area, and a control device node. The control area master node establishes a communication connection with the control device node, and each control sub-area is configured with a control device node, which is used to communicate with the devices in the control device sub-area.

[0039] Step S103, the control device sends a device data update instruction to the control sub-area according to a preset time period. After receiving the device data update instruction, the control device node of the control sub-area sends a status inspection command to the device in the control sub-area to which it belongs. After the device in the control sub-area feeds back the device operation data to the control device node, the control device node updates the device data in the control sub-area and sends the updated device data to the control area master node;

[0040] Step S104: The control area master node generates a new equipment inspection and monitoring list according to the updated equipment data, performs real-time monitoring on the equipment according to the new equipment inspection and monitoring list, obtains the real-time monitoring data of the equipment, compares the new equipment inspection and monitoring list with the equipment inspection and monitoring list before the update, and obtains the list cleared equipment information;

[0041] Step S105, retrieve the list to clear the device information history and the real-time monitoring data of the device to optimize the preset power system optimization, obtain the optimized power system optimization model, substitute the real-time monitoring data of the device into the optimized power system optimization model, and obtain the operating status prediction results of the devices in the Internet of Things.

[0042] Furthermore, the power optimization method based on the Internet of Things provided by the present invention, step S101, comprises:

[0043] Send communication information to each device on the device side, obtain communication information fed back by each device on the device side, extract device features from the communication information fed back by each device on the device side, obtain a list of devices corresponding to the feedback information, compare each device on the device side with the list of devices corresponding to the feedback information, and obtain devices with feedback information and devices without feedback information;

[0044] Perform communication protocol matching on the device without feedback information. If the matching is successful, configure the successfully matched communication protocol on the device without feedback information.

[0045] According to the preset time interval or trigger condition, a data request is sent to the device side, and the required data type is specified in the data request sent to the device side. The required data type includes device location data, device status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormal failure and equipment operation record data.

[0046] Furthermore, in the power optimization method based on the Internet of Things provided by the present invention, step S102 includes:

[0047] Analyze the equipment location data to determine the spatial distribution and relative position relationship of the equipment. According to the equipment location information and the actual needs of the power system, formulate the division rules of the control area. The division rules of the control area include geographical location, equipment type, and load conditions;

[0048] According to the control area division rules, the equipment is divided into different control areas. Each control area should contain equipment corresponding to the geographical location;

[0049] Set up the control area master node and control device node:

[0050] In each control area, a control area master node is set up to correspond to the overall control and coordination within the control area;

[0051] A control device node is configured for each control sub-area for communicating with and controlling the equipment in the corresponding control sub-area.

[0052] Furthermore, in the power optimization method based on the Internet of Things provided by the present invention, step S103 includes:

[0053] Setting a preset time period, and a frequency of sending device data update instructions to the control sub-area according to the preset time period;

[0054] At each preset time point, a device data update instruction is sent to the control device node of each control sub-area, where the device data update instruction includes the control device node performing a status inspection on the device in the control sub-area to which it belongs;

[0055] After sending the device data update instruction, wait for the status inspection feedback of the equipment in the control sub-area. After receiving the instruction, the control device node will send a status inspection command to the equipment in the area.

[0056] After receiving the status inspection command, the device performs a self-inspection and feeds back the device operation data to the control device node;

[0057] After receiving the operating data of all devices in the area to which it belongs, the control device node integrates and updates these data. The control device node uploads the updated device data to the control area master node, which then transmits it to the control area master node;

[0058] If any equipment abnormality or failure is found during the status inspection, the control device node will issue an abnormal situation warning.

[0059] Furthermore, in the power optimization method based on the Internet of Things provided by the present invention, step S104 comprises:

[0060] Retrieve the information history of the device that has been cleared from the list. The information history of the device that has been cleared from the list includes the operating data and fault records of the device that has been cleared or replaced;

[0061] Integrate the historical data of the cleared equipment with the real-time monitoring data of the current equipment, analyze the integrated data, and identify the equipment's operating trends, failure modes, and performance bottlenecks;

[0062] Based on the preset power system optimization objectives and constraints, use machine learning algorithms to build or update power system optimization models;

[0063] The historical data of the cleared equipment and the real-time monitoring data of the current equipment are integrated as input to train and optimize the model. The optimized model is verified using the historical data. If the verification is successful, the optimized power system optimization model is obtained.

[0064] Substitute the real-time monitoring data of the equipment into the optimized power system optimization model;

[0065] The optimized power system optimization model is used to calculate the operating status prediction results of the equipment in the Internet of Things, which include the probability of equipment failure, performance degradation trend and energy consumption prediction.

[0066] The invention provides an Internet of Things-based power optimization system and method, which have the following beneficial effects:

[0067] The power optimization system and method based on the Internet of Things of the present invention have significant beneficial effects, which are mainly reflected in the following aspects: First, by real-time collection and processing of power equipment operation data, the system can fully understand the operation status of the power system, thereby improving the overall operation efficiency of the power system. Secondly, the system automatically updates data and inspects equipment, which can save labor costs, and arranges maintenance plans in advance by predicting the operation status of the equipment, thereby reducing operation and maintenance costs. In addition, through real-time monitoring and early warning mechanisms, the system can quickly discover and respond to abnormal situations and improve the stability of power supply. At the same time, a large amount of data is analyzed using machine learning algorithms, which significantly improves the accuracy of predicting the operation status of the equipment. Finally, the system supports communication protocol matching and data collection for different devices, improves compatibility, and can be expanded and upgraded with technological progress. In summary, the present invention has significant advantages in improving the operation efficiency of the power system, reducing operation and maintenance costs, and improving operation stability, and provides strong support for the intelligent management and optimization of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0069] Figure 1 A schematic flow chart of a power optimization method based on the Internet of Things provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0071] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0072] In a first aspect, an Internet of Things-based power optimization system includes: a control device end and a background control end, a user terminal, and a device end, wherein the control device end establishes a communication connection with the background control end, the user terminal, and the device end, and the control device end processes data transmitted by the user terminal and the device end to obtain a prediction result of the operating state of the device in the Internet of Things, and the control device end sends the prediction result of the operating state of the device in the Internet of Things to the background control end, the user terminal, and the device end, wherein the control device end includes:

[0073] A data acquisition module is used to acquire power equipment operation data, which includes equipment location data, equipment status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormality and failure, and equipment operation record data;

[0074] The data acquisition module is responsible for acquiring comprehensive power equipment operation data, including: equipment location data, equipment status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormal failures, and equipment operation record data. By collecting these detailed data, the data acquisition module provides a solid data foundation for subsequent power equipment status analysis, fault prediction, performance optimization, etc., which helps to improve the operating efficiency and stability of the power system.

[0075] A control partition establishment module is used to divide the area where the equipment is located into control areas according to the equipment location data to obtain control areas. The control areas include a control area main node, a control sub-area and a control device node. The control area main node establishes a communication connection with the control device node. Each control sub-area is configured with a control device node. The control device node is used to communicate with the equipment in the control device sub-area.

[0076] In the power optimization system, the control partition establishment module divides the control area where the equipment is located mainly based on the location data of the equipment. The control area division ensures that the management of the power system is more accurate and efficient.

[0077] During the division process, the control partition establishment module first determines the control area, which includes the control area master node, control sub-area and control device node. The control area master node is the core of the entire control area, responsible for overall coordination and management, while the control sub-area is the result of further subdivision of the master area, and each control sub-area will be configured with a control device node.

[0078] The control device node is a key device in the control sub-area, which is responsible for communicating with other devices in the area. This means that each control device node has the ability to exchange information with the devices in the area, thereby achieving real-time monitoring and control of the devices.

[0079] In addition, a stable communication connection is established between the control area master node and the control device node. This connection ensures that the master node can send instructions to each control device node in a timely manner and receive feedback information from each node, thus forming a tight and efficient control system.

[0080] In general, the control partition establishment module enables every device in the power system to be effectively monitored and controlled through fine area division and node configuration, thereby improving the operating efficiency and safety of the power system.

[0081] The power equipment update module is used for the control device to send the equipment data update instruction to the control sub-area according to the preset time period. After the control device node of the control sub-area receives the equipment data update instruction, it sends a status inspection command to the equipment in the control sub-area to which it belongs. After the equipment in the control sub-area feeds back the equipment operation data to the control device node, the control device node updates the equipment data in the control sub-area and sends the updated equipment data to the control area master node;

[0082] The power equipment update module is mainly responsible for regularly updating the data of power equipment in the power optimization system to improve the real-time and accuracy of the data.

[0083] The power equipment update module will send equipment data update instructions to each control sub-area through the control device according to the preset time period. This time period can be set according to actual needs to ensure timely update of equipment data.

[0084] When the control device node in the control sub-area receives the device data update instruction, it will immediately send a status inspection command to the devices in the control sub-area to which it belongs. The status inspection command requires the device to perform a self-status check and feedback the latest operating data.

[0085] After receiving the status inspection command, the equipment in the control sub-area will perform self-inspection and feed back the latest equipment operation data to the control device node. The equipment operation data includes equipment status, electrical parameters, ambient temperature and humidity, energy consumption data, etc., which can fully reflect the current operating status of the equipment.

[0086] After collecting the operating data of all devices in the area, the control device node integrates and updates the data to ensure that the latest device operating data is stored. Then, the control device node sends the updated device data to the control area master node.

[0087] After receiving the equipment data uploaded by each control device node, the control area master node will summarize and analyze it. This data is not only used to monitor the operating status of the equipment in real time, but also can provide strong support for the optimization and fault prevention of the power system.

[0088] Through the workflow of the power equipment update module, the equipment data in the power system can always be kept up to date, thereby improving the operating efficiency and safety of the power system. At the same time, this also provides an accurate data basis for subsequent equipment status prediction and fault warning.

[0089] The power equipment monitoring module is used to control the regional master node to generate a new equipment inspection and monitoring list according to the updated equipment data, monitor the equipment in real time according to the new equipment inspection and monitoring list, obtain the real-time monitoring data of the equipment, compare the new equipment inspection and monitoring list with the equipment inspection and monitoring list before the update, and obtain the list clearing equipment information;

[0090] The power equipment monitoring module is mainly responsible for the following functions:

[0091] Generate equipment inspection and monitoring list: Generate a new equipment inspection and monitoring list based on the updated equipment data.

[0092] Real-time monitoring of equipment: Monitor the equipment in real time according to the new equipment inspection and monitoring list, and obtain real-time monitoring data of the equipment.

[0093] Comparative analysis: Compare the new equipment inspection and monitoring list with the list before the update to identify changes in the list, especially the equipment information that has been cleared or replaced.

[0094] Power equipment monitoring module workflow:

[0095] Data update: The control area master node first receives the updated device data from the control device node.

[0096] Function of control device node: The control device node is responsible for collecting the operating data of the equipment in its control sub-area, integrating and updating it, and then sending it to the control area master node.

[0097] Generate a new list: The control area master node generates a new equipment inspection and monitoring list based on the updated equipment data.

[0098] List content: The new list contains all the devices that need to be monitored and their related information.

[0099] Real-time monitoring: Based on the new equipment inspection and monitoring list, the system performs real-time monitoring of the equipment in the list.

[0100] Data collection: Real-time collection of equipment operating status data, including various electrical parameters, environmental conditions, etc.

[0101] Comparative analysis: Compare the newly generated equipment inspection and monitoring list with the previous list.

[0102] Purpose: To identify which devices have been added, removed, or replaced in order to update monitoring objectives.

[0103] Result output: Through comparative analysis, the system can output information about which equipment has been cleared or replaced. This information is very important for subsequent power system optimization.

[0104] The power equipment monitoring module collects and analyzes equipment data in real time, generates and updates equipment inspection and monitoring lists, and ensures effective monitoring of all key equipment in the power system. This process not only helps the system understand the equipment status in a timely manner, but also provides necessary data support for subsequent power system optimization.

[0105] The power system optimization module is used to retrieve the list to clear the device information history and the real-time monitoring data of the equipment to optimize the preset power system optimization, obtain the optimized power system optimization model, substitute the real-time monitoring data of the equipment into the optimized power system optimization model, and obtain the operating status prediction results of the equipment in the Internet of Things.

[0106] Optimize power system model: Use the historical data of the cleared equipment and the real-time monitoring data of the current equipment to optimize the preset power system optimization model to improve the accuracy of the model prediction.

[0107] Predict equipment operating status: Through the optimized power system optimization model, the operating status of the equipment in the Internet of Things is predicted, including the probability of equipment failure, performance degradation trend and energy consumption prediction.

[0108] Improve system efficiency and reliability: Based on accurate prediction results, the operation strategy of the power system can be adjusted in time to improve the efficiency and reliability of the overall system.

[0109] Workflow of the power system optimization module;

[0110] Data integration: Retrieve historical data: retrieve the information history of the cleared device, including the operation data and fault records of the cleared or replaced device. Integrate real-time monitoring data: integrate the historical data of the cleared device with the real-time monitoring data of the current device.

[0111] Data Analysis: Identify Equipment Trends: Analyze the integrated data to identify equipment operating trends, failure modes, and performance bottlenecks.

[0112] Model optimization: Build or update the model: Based on the preset power system optimization objectives and constraints, use machine learning algorithms to build or update the power system optimization model.

[0113] Model training and validation: Use the integrated data as input to train and optimize the model, and use historical data to validate the optimized model.

[0114] Prediction calculation: Substitute the real-time monitoring data: Substitute the real-time monitoring data of the equipment into the optimized power system optimization model. Calculate the prediction results: Through model calculation, the operating status prediction results of the equipment in the Internet of Things are obtained.

[0115] Result output: The prediction results (including equipment failure probability, performance degradation trend and energy consumption prediction) are sent to the background control end, user terminal and device end for reference and decision-making by relevant personnel.

[0116] Through this series of steps, the power system optimization module can effectively improve the intelligent management level of the power system and ensure the stable and efficient operation of the system.

[0117] Specifically, the present invention provides the power optimization system based on the Internet of Things, wherein the data acquisition module is further used for:

[0118] Send communication information to each device on the device side, obtain communication information fed back by each device on the device side, extract device features from the communication information fed back by each device on the device side, obtain a list of devices corresponding to the feedback information, compare each device on the device side with the list of devices corresponding to the feedback information, and obtain devices with feedback information and devices without feedback information;

[0119] Perform communication protocol matching on the device without feedback information. If the matching is successful, configure the successfully matched communication protocol on the device without feedback information.

[0120] According to the preset time interval or trigger condition, a data request is sent to the device side, and the required data type is specified in the data request sent to the device side. The required data type includes device location data, device status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormal failure and equipment operation record data.

[0121] Specifically, the present invention provides the power optimization system based on the Internet of Things, wherein the control partition establishment module is further used for:

[0122] Analyze the equipment location data to determine the spatial distribution and relative position relationship of the equipment. According to the equipment location information and the actual needs of the power system, formulate the division rules of the control area. The division rules of the control area include geographical location, equipment type, and load conditions;

[0123] According to the control area division rules, the equipment is divided into different control areas. Each control area should contain equipment corresponding to the geographical location;

[0124] Set up the control area master node and control device node:

[0125] In each control area, a control area master node is set up to correspond to the overall control and coordination within the control area;

[0126] A control device node is configured for each control sub-area for communicating with and controlling the equipment in the corresponding control sub-area.

[0127] Specifically, the present invention provides the power optimization system based on the Internet of Things, wherein the power equipment update module is further used for:

[0128] Setting a preset time period, and a frequency of sending device data update instructions to the control sub-area according to the preset time period;

[0129] At each preset time point, a device data update instruction is sent to the control device node of each control sub-area, where the device data update instruction includes the control device node performing a status inspection on the device in the control sub-area to which it belongs;

[0130] After sending the device data update instruction, wait for the status inspection feedback of the equipment in the control sub-area. After receiving the instruction, the control device node will send a status inspection command to the equipment in the area.

[0131] After receiving the status inspection command, the device performs a self-inspection and feeds back the device operation data to the control device node;

[0132] After receiving the operating data of all devices in the area to which it belongs, the control device node integrates and updates these data. The control device node uploads the updated device data to the control area master node, which then transmits it to the control area master node;

[0133] If any equipment abnormality or failure is found during the status inspection, the control device node will issue an abnormal situation warning.

[0134] Specifically, the present invention provides the power optimization system based on the Internet of Things, wherein the power system optimization module is further used for:

[0135] Retrieve the information history of the device that has been cleared from the list. The information history of the device that has been cleared from the list includes the operating data and fault records of the device that has been cleared or replaced;

[0136] Integrate the historical data of the cleared equipment with the real-time monitoring data of the current equipment, analyze the integrated data, and identify the equipment's operating trends, failure modes, and performance bottlenecks;

[0137] Based on the preset power system optimization objectives and constraints, use machine learning algorithms to build or update power system optimization models;

[0138] The historical data of the cleared equipment and the real-time monitoring data of the current equipment are integrated as input to train and optimize the model. The optimized model is verified using the historical data. If the verification is successful, the optimized power system optimization model is obtained.

[0139] Substitute the real-time monitoring data of the equipment into the optimized power system optimization model;

[0140] The optimized power system optimization model is used to calculate the operating status prediction results of the equipment in the Internet of Things, which include the probability of equipment failure, performance degradation trend and energy consumption prediction.

[0141] In a second aspect, a power optimization method based on the Internet of Things is applied to the power optimization system based on the Internet of Things, comprising:

[0142] Step S101, obtaining power equipment operation data, the power equipment operation data including equipment location data, equipment status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormality and failure, and equipment operation record data;

[0143] Step S102: According to the device location data, the area where the device is located is divided into control areas to obtain control areas, where the control areas include a control area master node, a control sub-area, and a control device node. The control area master node establishes a communication connection with the control device node, and each control sub-area is configured with a control device node, which is used to communicate with the devices in the control device sub-area.

[0144] Step S103, the control device sends a device data update instruction to the control sub-area according to a preset time period. After receiving the device data update instruction, the control device node of the control sub-area sends a status inspection command to the device in the control sub-area to which it belongs. After the device in the control sub-area feeds back the device operation data to the control device node, the control device node updates the device data in the control sub-area and sends the updated device data to the control area master node;

[0145] Step S104: The control area master node generates a new equipment inspection and monitoring list according to the updated equipment data, performs real-time monitoring on the equipment according to the new equipment inspection and monitoring list, obtains the real-time monitoring data of the equipment, compares the new equipment inspection and monitoring list with the equipment inspection and monitoring list before the update, and obtains the list cleared equipment information;

[0146] Step S105, retrieve the list to clear the device information history and the real-time monitoring data of the device to optimize the preset power system optimization, obtain the optimized power system optimization model, substitute the real-time monitoring data of the device into the optimized power system optimization model, and obtain the operating status prediction results of the devices in the Internet of Things.

[0147] Specifically, the power optimization method based on the Internet of Things provided by the present invention, step S101, includes:

[0148] Send communication information to each device on the device side, obtain communication information fed back by each device on the device side, extract device features from the communication information fed back by each device on the device side, obtain a list of devices corresponding to the feedback information, compare each device on the device side with the list of devices corresponding to the feedback information, and obtain devices with feedback information and devices without feedback information;

[0149] Perform communication protocol matching on the device without feedback information. If the matching is successful, configure the successfully matched communication protocol on the device without feedback information.

[0150] According to the preset time interval or trigger condition, a data request is sent to the device side, and the required data type is specified in the data request sent to the device side. The required data type includes device location data, device status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormal failure and equipment operation record data.

[0151] Specifically, the power optimization method based on the Internet of Things provided by the present invention, step S102, includes:

[0152] Analyze the equipment location data to determine the spatial distribution and relative position relationship of the equipment. According to the equipment location information and the actual needs of the power system, formulate the division rules of the control area. The division rules of the control area include geographical location, equipment type, and load conditions;

[0153] According to the control area division rules, the equipment is divided into different control areas. Each control area should contain equipment corresponding to the geographical location;

[0154] Set up the control area master node and control device node:

[0155] In each control area, a control area master node is set up to correspond to the overall control and coordination within the control area;

[0156] A control device node is configured for each control sub-area for communicating with and controlling the equipment in the corresponding control sub-area.

[0157] Specifically, the power optimization method based on the Internet of Things provided by the present invention, step S103, includes:

[0158] Setting a preset time period, and a frequency of sending device data update instructions to the control sub-area according to the preset time period;

[0159] At each preset time point, a device data update instruction is sent to the control device node of each control sub-area, where the device data update instruction includes the control device node performing a status inspection on the device in the control sub-area to which it belongs;

[0160] After sending the device data update instruction, wait for the status inspection feedback of the equipment in the control sub-area. After receiving the instruction, the control device node will send a status inspection command to the equipment in the area.

[0161] After receiving the status inspection command, the device performs a self-inspection and feeds back the device operation data to the control device node;

[0162] After receiving the operating data of all devices in the area to which it belongs, the control device node integrates and updates these data. The control device node uploads the updated device data to the control area master node, which then transmits it to the control area master node;

[0163] If any equipment abnormality or failure is found during the status inspection, the control device node will issue an abnormal situation warning.

[0164] Specifically, the power optimization method based on the Internet of Things provided by the present invention, step S104, includes:

[0165] Retrieve the information history of the device that has been cleared from the list. The information history of the device that has been cleared from the list includes the operating data and fault records of the device that has been cleared or replaced;

[0166] Integrate the historical data of the cleared equipment with the real-time monitoring data of the current equipment, analyze the integrated data, and identify the equipment's operating trends, failure modes, and performance bottlenecks;

[0167] Based on the preset power system optimization objectives and constraints, use machine learning algorithms to build or update power system optimization models;

[0168] The historical data of the cleared equipment and the real-time monitoring data of the current equipment are integrated as input to train and optimize the model. The optimized model is verified using the historical data. If the verification is successful, the optimized power system optimization model is obtained.

[0169] Substitute the real-time monitoring data of the equipment into the optimized power system optimization model;

[0170] The optimized power system optimization model is used to calculate the operating status prediction results of the equipment in the Internet of Things, which include the probability of equipment failure, performance degradation trend and energy consumption prediction.

[0171] The present invention effectively solves the problem of inaccurate prediction of the operating status of power equipment caused by the large number of power plant equipment, different models, different usage conditions, and dynamic changes in the number of equipment and communication status:

[0172] First, the data acquisition module comprehensively collects various operating data of power equipment, providing a rich data source for subsequent prediction and analysis. Secondly, the control partition establishment module is used to dynamically divide the area where the equipment is located, and set up the control area master node and control device node to ensure the effectiveness and pertinence of the control area.

[0173] In addition, the power equipment update module sends equipment data update instructions at a preset time period to maintain the real-time and accuracy of equipment data. At the same time, the power equipment monitoring module and the control area master node generate a new equipment inspection and monitoring list based on the updated equipment data, monitor the equipment status in real time, and compare it with historical data.

[0174] In order to further improve the accuracy of the prediction, the present invention adopts a machine learning algorithm to construct or update the power system optimization model, which can integrate historical data and real-time monitoring data to more accurately identify the operating trends, failure modes and performance bottlenecks of the equipment.

[0175] In addition, the data acquisition module is also responsible for matching the communication protocols for devices that have no feedback information to ensure that all devices can communicate normally and avoid data loss or communication barriers caused by device compatibility issues.

[0176] Finally, through regular updates, real-time monitoring, and machine learning optimization, the entire system can adapt to the dynamically changing environment, and can promptly warn of equipment anomalies or failures to ensure the stable operation of the power system.

[0177] In summary, the present invention effectively solves the problem of inaccurate prediction of the operating status of power equipment through a series of comprehensive measures, including comprehensive data collection, dynamic area division, regular data update, real-time monitoring and status prediction, machine learning optimization model, communication protocol matching, and dynamic adaptation and early warning system.

[0178] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations, and the above-described embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention.

Claims

1. A power optimization system based on the Internet of Things, characterized in that: include: The control device end establishes communication connections with the background control end, the user terminal, and the device end. The control device end processes the data transmitted by the user terminal and the device end to obtain the predicted results of the running status of the devices in the Internet of Things. The control device end sends the predicted results of the running status of the devices in the Internet of Things to the background control end, the user terminal, and the device end. The control device end includes: A data acquisition module is used to acquire power equipment operation data, which includes equipment location data, equipment status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormality and failure, and equipment operation record data; A control partition establishment module is used to divide the area where the equipment is located into control areas according to the equipment location data to obtain control areas. The control areas include a control area main node, a control sub-area and a control device node. The control area main node establishes a communication connection with the control device node. Each control sub-area is configured with a control device node. The control device node is used to communicate with the equipment in the control device sub-area. The power equipment update module is used for the control device to send the equipment data update instruction to the control sub-area according to the preset time period. After the control device node of the control sub-area receives the equipment data update instruction, it sends a status inspection command to the equipment in the control sub-area to which it belongs. After the equipment in the control sub-area feeds back the equipment operation data to the control device node, the control device node updates the equipment data in the control sub-area and sends the updated equipment data to the control area master node; The power equipment monitoring module is used to control the regional master node to generate a new equipment inspection and monitoring list according to the updated equipment data, monitor the equipment in real time according to the new equipment inspection and monitoring list, obtain the real-time monitoring data of the equipment, compare the new equipment inspection and monitoring list with the equipment inspection and monitoring list before the update, and obtain the list clearing equipment information; The power system optimization module is used to retrieve the list to clear the device information history and the real-time monitoring data of the equipment to optimize the preset power system optimization, obtain the optimized power system optimization model, substitute the real-time monitoring data of the equipment into the optimized power system optimization model, and obtain the operating status prediction results of the equipment in the Internet of Things.

2. The power optimization system based on the Internet of Things according to claim 1, characterized in that: The data acquisition module is further used for: Send communication information to each device on the device side, obtain communication information fed back by each device on the device side, extract device features from the communication information fed back by each device on the device side, obtain a list of devices corresponding to the feedback information, compare each device on the device side with the list of devices corresponding to the feedback information, and obtain devices with feedback information and devices without feedback information; Perform communication protocol matching on the device without feedback information. If the matching is successful, configure the successfully matched communication protocol on the device without feedback information. According to the preset time interval or trigger condition, a data request is sent to the device side, and the required data type is specified in the data request sent to the device side. The required data type includes device location data, device status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormal failure and equipment operation record data.

3. The power optimization system based on the Internet of Things according to claim 1, characterized in that: The control partition establishment module is also used for: Analyze the equipment location data to determine the spatial distribution and relative position relationship of the equipment. According to the equipment location information and the actual needs of the power system, formulate the division rules of the control area. The division rules of the control area include geographical location, equipment type, and load conditions; According to the control area division rules, the equipment is divided into different control areas. Each control area should contain equipment corresponding to the geographical location; Set up the control area master node and control device node: In each control area, a control area master node is set up to correspond to the overall control and coordination within the control area; A control device node is configured for each control sub-area for communicating with and controlling the equipment in the corresponding control sub-area.

4. The power optimization system based on the Internet of Things according to claim 1, characterized in that: The power equipment updating module is also used for: Setting a preset time period, and a frequency of sending device data update instructions to the control sub-area according to the preset time period; At each preset time point, a device data update instruction is sent to the control device node of each control sub-area, where the device data update instruction includes the control device node performing a status inspection on the device in the control sub-area to which it belongs; After sending the device data update command, wait for the status inspection feedback of the devices in the control sub-area. After receiving the command, the control device node will send a status inspection command to the devices in the area to which it belongs; After receiving the status inspection command, the device performs a self-inspection and feeds back the device operation data to the control device node; After receiving the operating data of all devices in the area to which it belongs, the control device node integrates and updates these data. The control device node uploads the updated device data to the control area master node, which then transmits it to the control area master node; If any equipment abnormality or failure is found during the status inspection, the control device node will issue an abnormal situation warning.

5. The power optimization system based on the Internet of Things according to claim 1, characterized in that: The power system optimization module is also used for: Retrieve the information history of the device that has been cleared from the list. The information history of the device that has been cleared from the list includes the operating data and fault records of the device that has been cleared or replaced; Integrate the historical data of the cleared equipment with the real-time monitoring data of the current equipment, analyze the integrated data, and identify the equipment's operating trends, failure modes, and performance bottlenecks; Based on the preset power system optimization objectives and constraints, use machine learning algorithms to build or update power system optimization models; The historical data of the cleared equipment and the real-time monitoring data of the current equipment are integrated as input to train and optimize the model. The optimized model is verified using the historical data. If the verification is successful, the optimized power system optimization model is obtained. Substitute the real-time monitoring data of the equipment into the optimized power system optimization model; The optimized power system optimization model is used to calculate the operating status prediction results of the equipment in the Internet of Things, which include the probability of equipment failure, performance degradation trend and energy consumption prediction.

6. A power optimization method based on the Internet of Things, characterized in that: Applied in the power optimization system based on the Internet of Things as claimed in any one of claims 1 to 5, comprising: Step S101, obtaining power equipment operation data, the power equipment operation data including equipment location data, equipment status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormality and failure, and equipment operation record data; Step S102: According to the device location data, the area where the device is located is divided into control areas to obtain control areas, where the control areas include a control area master node, a control sub-area, and a control device node. The control area master node establishes a communication connection with the control device node, and each control sub-area is configured with a control device node, which is used to communicate with the devices in the control device sub-area. Step S103, the control device sends a device data update instruction to the control sub-area according to a preset time period. After receiving the device data update instruction, the control device node of the control sub-area sends a status inspection command to the device in the control sub-area to which it belongs. After the device in the control sub-area feeds back the device operation data to the control device node, the control device node updates the device data in the control sub-area and sends the updated device data to the control area master node; Step S104: The control area master node generates a new equipment inspection and monitoring list according to the updated equipment data, performs real-time monitoring on the equipment according to the new equipment inspection and monitoring list, obtains the real-time monitoring data of the equipment, compares the new equipment inspection and monitoring list with the equipment inspection and monitoring list before the update, and obtains the list cleared equipment information; Step S105, retrieve the list to clear the device information history and the real-time monitoring data of the device to optimize the preset power system optimization, obtain the optimized power system optimization model, substitute the real-time monitoring data of the device into the optimized power system optimization model, and obtain the operating status prediction results of the devices in the Internet of Things.

7. The power optimization method based on the Internet of Things according to claim 6, characterized in that: The step S101 includes: Send communication information to each device on the device side, obtain communication information fed back by each device on the device side, extract device features from the communication information fed back by each device on the device side, obtain a list of devices corresponding to the feedback information, compare each device on the device side with the list of devices corresponding to the feedback information, obtain devices with feedback information and devices without feedback information; match the communication protocol of the device without feedback information, and if the match is successful, configure the successfully matched communication protocol on the device without feedback information; According to the preset time interval or trigger condition, a data request is sent to the device side, and the required data type is specified in the data request sent to the device side. The required data type includes device location data, device status data, electrical parameter data, ambient temperature data, ambient humidity data, power equipment energy consumption data, equipment abnormal failure and equipment operation record data.

8. The power optimization method based on the Internet of Things according to claim 6, characterized in that: The step S102 includes: Analyze the equipment location data to determine the spatial distribution and relative position relationship of the equipment. According to the equipment location information and the actual needs of the power system, formulate the division rules of the control area. The division rules of the control area include geographical location, equipment type, and load conditions; According to the control area division rules, the equipment is divided into different control areas. Each control area should contain equipment corresponding to the geographical location; Set up the control area master node and control device node: In each control area, a control area master node is set up to correspond to the overall control and coordination within the control area; A control device node is configured for each control sub-area for communicating with and controlling the equipment in the corresponding control sub-area.

9. The power optimization method based on the Internet of Things according to claim 6, characterized in that: The step S103 includes: Setting a preset time period, and a frequency of sending device data update instructions to the control sub-area according to the preset time period; At each preset time point, a device data update instruction is sent to the control device node of each control sub-area, where the device data update instruction includes the control device node performing a status inspection on the device in the control sub-area to which it belongs; After sending the device data update command, wait for the status inspection feedback of the devices in the control sub-area. After receiving the command, the control device node will send a status inspection command to the devices in the area to which it belongs; After receiving the status inspection command, the device performs a self-inspection and feeds back the device operation data to the control device node; After receiving the operating data of all devices in the area to which it belongs, the control device node integrates and updates these data. The control device node uploads the updated device data to the control area master node, which then transmits it to the control area master node; If any equipment abnormality or failure is found during the status inspection, the control device node will issue an abnormal situation warning.

10. The power optimization method based on the Internet of Things according to claim 6, characterized in that: The step S104 includes: Retrieve the information history of the device that has been cleared from the list. The information history of the device that has been cleared from the list includes the operating data and fault records of the device that has been cleared or replaced; Integrate the historical data of the cleared equipment with the real-time monitoring data of the current equipment, analyze the integrated data, and identify the equipment's operating trends, failure modes, and performance bottlenecks; Based on the preset power system optimization objectives and constraints, use machine learning algorithms to build or update power system optimization models; The historical data of the cleared equipment and the real-time monitoring data of the current equipment are integrated as input to train and optimize the model. The optimized model is verified using the historical data. If the verification is successful, the optimized power system optimization model is obtained. Substitute the real-time monitoring data of the equipment into the optimized power system optimization model; The optimized power system optimization model is used to calculate the operating status prediction results of the equipment in the Internet of Things, which include the probability of equipment failure, performance degradation trend and energy consumption prediction.

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