Iot park energy consumption monitoring and intelligent control service system based on digital twinning

Abstract

The application discloses an Internet of Things park energy consumption monitoring and intelligent regulation and control service system based on digital twinning, relates to the technical field of Internet of Things park energy consumption analysis, and comprises a node screening module which carries out position correction processing on the initial node positions inside an Internet of Things park through an energy supply link of the Internet of Things park to obtain real node positions inside the Internet of Things park. The application first equivalently converts all devices inside the Internet of Things park into nodes, then compares the energy supply modes of the nodes, divides part of the nodes into loads, reduces the calculation amount of subsequent node energy consumption calculation, and finally compares the initial energy consumption and real-time energy consumption of the nodes to determine whether the energy consumed by the nodes when performing tasks meets the standard, and if not, the device at the node position is abnormal, device repair information is sent to repair personnel, the abnormal device can be repaired in time, and the energy loss of the Internet of Things park is reduced.

Description

Technical Field

[0001] This invention relates to the field of IoT park energy consumption analysis technology, specifically to an IoT park energy consumption monitoring and intelligent control service system based on digital twins. Background Technology

[0002] IoT parks can be divided into two main categories. The first category consists of various parks that use IoT technology to achieve intelligent operation (such as industrial parks, business parks, scenic spots, etc.), aiming to improve management efficiency and user experience. The second category consists of specialized parks that gather IoT industry chain enterprises and integrate R&D, manufacturing, and application, aiming to promote technological innovation and industrial upgrading.

[0003] The Internet of Things (IoT) park will install different types of equipment, and these devices all require energy supply. However, when these devices malfunction, they will consume too much energy, leading to increased maintenance costs for the IoT park. Summary of the Invention

[0004] To address the aforementioned technical issues, this technical solution provides an IoT-based energy consumption monitoring and intelligent control service system for industrial parks, which solves the problems mentioned in the background section.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The IoT-based campus energy consumption monitoring and intelligent control service system based on digital twins includes: The intelligent control terminal is used to control the data transmission and information interaction between various modules. The intelligent control terminal is also used to perform energy consumption calculation and energy consumption comparison of the real node locations within the IoT park to determine whether there are any abnormal energy consumption locations within the IoT park. The database system is used to store the internal structure drawings and internal circuit distribution drawings of the Internet of Things (IoT) park. The node filtering module performs position correction processing on the initial node positions inside the IoT park through the energy supply chain route of the IoT park to obtain the real node positions inside the IoT park. The node energy consumption calculation module is used to perform load energy consumption calculation on the actual node locations within the IoT park to obtain the initial energy consumption and real-time energy consumption of the actual nodes. The node energy consumption analysis module is used to compare and analyze the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park.

[0006] Preferably, the node screening module performs position correction processing on the initial node positions within the IoT park through the energy supply chain route of the IoT park to obtain the actual node positions within the IoT park. Specifically, this includes the following steps: Based on the intelligent control terminal, data retrieval and processing are performed on the database system to obtain the internal structure drawings and internal circuit distribution drawings of the IoT park. Based on intelligent control terminals, the devices in the internal structure drawings of the Internet of Things (IoT) park are marked using device identifiers to determine the initial node positions within the IoT park. Based on the intelligent control terminal, the initial node positions inside the IoT park are corrected by using the internal circuit distribution diagram of the IoT park to obtain the actual node positions inside the IoT park.

[0007] Preferably, the step of correcting the initial node positions within the IoT park based on the internal circuit distribution diagram of the IoT park using the intelligent control terminal to obtain the actual node positions within the IoT park specifically includes the following steps: Based on intelligent control terminals, information is extracted and processed from the internal circuit distribution diagram of the Internet of Things (IoT) park using circuit wiring characteristics to obtain the energy supply chain route of the IoT park. Based on the intelligent control terminal, the initial node locations within the IoT park are screened through the energy supply chain route of the IoT park to obtain the locations of energy-consuming nodes within the IoT park. Based on the node screening module, the location of energy-consuming nodes inside the IoT park is analyzed by using the internal circuit distribution diagram of the IoT park to obtain the actual node locations inside the IoT park.

[0008] Preferably, the step of using a smart control terminal to perform node screening processing on the initial node locations within the IoT park through the energy supply chain path of the IoT park to obtain the locations of energy-consuming nodes within the IoT park specifically includes the following steps: Based on the intelligent control terminal, the energy supply chain route of the Internet of Things (IoT) park performs location matching processing on the initial node locations within the IoT park. If the energy supply chain of the IoT park intersects with all the initial node locations within the IoT park, and all the devices at the initial node locations within the IoT park require energy consumption, then based on the intelligent control terminal, the initial node locations within the IoT park are set as the energy-consuming node locations within the IoT park. If there are nodes in the energy supply chain of the IoT park that do not intersect with the initial node location within the IoT park, and the devices at the initial node location within the IoT park that do not intersect do not consume energy, then based on the intelligent control terminal, the initial node location within the IoT park that intersects with the energy supply chain of the IoT park will be set as the energy-consuming node location within the IoT park.

[0009] Preferably, the node-based filtering module performs node analysis processing on the locations of energy-consuming nodes within the IoT park using the internal circuit distribution diagram of the IoT park to obtain the actual node locations within the IoT park. This specifically includes the following steps: Based on the node filtering module, the internal structure map of the IoT park is marked using energy supply equipment identifiers to determine the location of the energy supply equipment. Based on the node filtering module, location matching is performed on the location of energy supply equipment, the location of energy-consuming nodes within the IoT park, and the energy supply chain route of the IoT park. If all starting points of the energy supply chain in the IoT park are the locations of energy supply equipment, and all ending points of the energy supply chain in the IoT park are the locations of energy-consuming nodes within the IoT park, and the energy consumed by the equipment at the energy-consuming nodes within the IoT park is supplied by the energy supply equipment, then based on the node filtering module, the locations of energy-consuming nodes within the IoT park are set as the actual node locations within the IoT park. If any of the starting points of the energy supply chain path in the IoT park are not located at the location of an energy supply device, then the device at the energy-consuming node location within the IoT park that is not located at the location of an energy supply device will be set as a load. Based on the node filtering module, the starting point of the energy supply chain path in the IoT park that is located at the location of an energy supply device, and all the ending points of the energy supply chain path in the IoT park that are energy-consuming nodes within the IoT park, will be set as the actual node locations within the IoT park.

[0010] Preferably, the node energy consumption calculation module is used to perform load energy consumption calculation processing on the actual node locations within the IoT park, and to obtain the initial energy consumption and real-time energy consumption of the actual nodes. Specifically, this includes the following steps: Based on intelligent control terminals, information is extracted and processed from the internal structure drawings of the IoT park using the actual node locations within the park as features, to obtain the load data of the actual nodes. Based on the intelligent control terminal, the load data of real nodes is extracted and processed with the characteristic of not performing tasks, so as to obtain the energy consumption of all loads when there are no tasks. Based on the node energy consumption calculation module, the energy consumption of all loads when there are no tasks is summed to obtain the initial energy consumption of the actual node. Based on the node energy consumption calculation module, the load data of real nodes is calculated and processed to obtain the real-time energy consumption of real nodes.

[0011] Preferably, the node-based energy consumption calculation module processes the load data of real nodes to obtain the real-time energy consumption of real nodes, specifically including the following steps: Based on the intelligent control terminal, the load data of real nodes is extracted and processed with the execution of tasks as the feature to obtain the energy consumption of loads that are not executing tasks, the energy consumption of loads that are executing tasks, and the content of the tasks being executed. Based on the node energy consumption calculation module, the energy consumption of the load that is not performing a task and the energy consumption of the load that is performing a task are summed to obtain the real-time energy consumption of the actual node.

[0012] Preferably, the node energy consumption analysis module is used to compare and analyze the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park. Specifically, this includes the following steps: Based on the intelligent control terminal, the difference between the initial energy consumption and the real-time energy consumption of the real node is calculated to obtain the energy consumption difference when the real node performs the task. Based on the intelligent control terminal, the task content being executed is evaluated and processed to obtain the predicted energy consumption value when the actual node is executing the task. Based on the node energy consumption analysis module, the difference in energy consumption when the actual node performs a task and the predicted energy consumption when the actual node performs a task are compared and analyzed to determine whether there are any abnormal energy consumption locations within the IoT park.

[0013] Preferably, the node-based energy consumption analysis module compares and analyzes the energy consumption difference between actual nodes performing tasks and the predicted energy consumption of actual nodes performing tasks to determine whether there are any abnormal energy consumption locations within the IoT park. This specifically includes the following steps: Based on the node energy consumption analysis module, the difference in energy consumption when the actual node performs a task and the predicted value of energy consumption when the actual node performs a task are judged and processed. If the energy consumption difference when the actual node performs a task is approximately equal to the predicted energy consumption when the actual node performs a task, or if the difference between the energy consumption difference when the actual node performs a task and the predicted energy consumption when the actual node performs a task is within 10 percent of the predicted energy consumption when the actual node performs a task, there are no abnormal energy consumption locations within the IoT park. If the difference between the energy consumption of the actual node performing the task and the predicted energy consumption of the actual node performing the task is greater than 10% of the predicted energy consumption of the actual node performing the task, there is an abnormal energy consumption location within the IoT park. Based on the node energy consumption analysis module, the abnormal energy consumption location is uploaded to the intelligent control terminal, and the intelligent control terminal sends maintenance information of the abnormal energy consumption location to the electronic equipment of the maintenance personnel.

[0014] Furthermore, a method for energy consumption monitoring and intelligent control services in IoT parks based on digital twins is proposed. This method employs the aforementioned digital twin-based IoT park energy consumption monitoring and intelligent control service system to monitor and intelligently control energy consumption in IoT parks, including: S100. Determine the initial node location within the IoT park. Based on the intelligent control terminal, perform position correction processing on the initial node location within the IoT park through the energy supply chain route of the IoT park to obtain the actual node location within the IoT park. S200: Based on the intelligent control terminal, the load energy consumption calculation of the real node locations within the IoT park is performed to obtain the initial energy consumption and real-time energy consumption of the real nodes. S300, based on the intelligent control terminal, compares and analyzes the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park.

[0015] Compared with existing technologies, this invention provides an IoT-based campus energy consumption monitoring and intelligent control service system based on digital twins, which has the following beneficial effects: This invention first converts all devices within an IoT park into equivalent nodes. Then, it compares the energy supply methods of these nodes, classifies some nodes as loads, and reduces the computational load of subsequent node energy consumption calculations. Finally, it compares the initial and real-time energy consumption of the nodes to determine whether the energy consumed by the nodes when performing tasks meets the standards. If it does not meet the standards, the device at the node location is found to be abnormal, and equipment maintenance information is sent to maintenance personnel so that the abnormal device can be repaired in a timely manner, thereby reducing energy consumption in the IoT park. Attached Figure Description

[0016] Figure 1 This is a structural block diagram of the IoT-based campus energy consumption monitoring and intelligent control service system based on digital twins proposed in this invention. Figure 2 This is a flowchart illustrating steps S100-S300 of the IoT-based energy consumption monitoring and intelligent control service method for parks based on digital twins proposed in this invention. Detailed Implementation

[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0018] Reference Figure 1 As shown, the IoT-based campus energy consumption monitoring and intelligent control service system based on digital twins includes: The intelligent control terminal is used to control the data transmission and information interaction between various modules. The intelligent control terminal is also used to perform energy consumption calculation and energy consumption comparison of the real node locations within the IoT park to determine whether there are any abnormal energy consumption locations within the IoT park. The database system is used to store the internal structure drawings and internal circuit distribution drawings of the Internet of Things (IoT) park. The node filtering module performs position correction processing on the initial node positions inside the IoT park through the energy supply chain route of the IoT park to obtain the real node positions inside the IoT park. The node energy consumption calculation module is used to perform load energy consumption calculation on the actual node locations within the IoT park to obtain the initial energy consumption and real-time energy consumption of the actual nodes. The node energy consumption analysis module is used to compare and analyze the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park. Those skilled in the art will understand that various types of equipment are installed within an IoT park to maintain its normal operation. However, when some equipment in the IoT park malfunctions, its energy consumption increases. If the malfunctioning equipment is not repaired in a timely manner, the electricity cost of the IoT park will increase. Therefore, by comparing the energy consumed by the equipment when it is first put into use (i.e., the initial energy consumption of the real node) with the energy consumed by the equipment when performing tasks (i.e., the real-time energy consumption of the real node), it can be determined whether the equipment is malfunctioning. If the equipment is malfunctioning, the difference between the initial energy consumption and the real-time energy consumption of the real node does not meet the standard. In this case, only the equipment corresponding to the real-time energy consumption of the real node that does not meet the standard needs to be repaired to achieve timely repair of the malfunctioning equipment, thereby increasing the electricity cost of the IoT.

[0019] Example 1 The node selection module performs location correction processing on the initial node locations within the IoT park based on the energy supply chain route of the IoT park to obtain the actual node locations within the IoT park. Specifically, this includes the following steps: Based on the intelligent control terminal, data retrieval and processing are performed on the database system to obtain the internal structure drawings and internal circuit distribution drawings of the IoT park. Based on intelligent control terminals, the devices in the internal structure drawings of the Internet of Things (IoT) park are marked using device identifiers to determine the initial node positions within the IoT park. Based on the intelligent control terminal, the initial node positions inside the IoT park are corrected by using the internal circuit distribution diagram of the IoT park to obtain the actual node positions inside the IoT park. It is understandable that different types of devices will be installed inside the IoT park. Some of these devices are quite large. To facilitate subsequent analysis, these devices are converted into nodes. The wiring between nodes is easier to observe, which allows us to determine the relationship between different devices more quickly. The process of obtaining the actual node locations within the IoT park by correcting the initial node locations based on the internal circuit distribution diagram of the IoT park using a smart control terminal includes the following steps: Based on intelligent control terminals, information is extracted and processed from the internal circuit distribution diagram of the Internet of Things (IoT) park using circuit wiring characteristics to obtain the energy supply chain route of the IoT park. Based on the intelligent control terminal, the initial node locations within the IoT park are screened through the energy supply chain route of the IoT park to obtain the locations of energy-consuming nodes within the IoT park. Based on the node screening module, the location of energy-consuming nodes inside the IoT park is analyzed and processed by the internal circuit distribution diagram of the IoT park to obtain the actual node location inside the IoT park. Understandably, the flow of electricity within the IoT park is through the IoT park's energy supply chain. Therefore, by examining the IoT park's energy supply chain, it is possible to identify which nodes are actually consuming energy within the IoT park and which are dummy nodes. It is worth noting that these dummy nodes are also devices installed within the IoT park, but these devices are not in use. Instead, they serve as backup devices. When some devices fail, these devices are connected to the IoT park's energy supply chain to maintain the normal operation of the IoT park. Therefore, these dummy nodes are backup devices that are not connected to the IoT park's energy supply chain. Specifically, based on intelligent control terminals, the process of selecting initial node locations within the IoT park through the energy supply chain route of the IoT park to obtain the locations of energy-consuming nodes within the IoT park includes the following steps: Based on the intelligent control terminal, the energy supply chain route of the Internet of Things (IoT) park performs location matching processing on the initial node locations within the IoT park. If the energy supply chain of the IoT park intersects with all the initial node locations within the IoT park, and all the devices at the initial node locations within the IoT park require energy consumption, then based on the intelligent control terminal, the initial node locations within the IoT park are set as the energy-consuming node locations within the IoT park. If there are nodes in the energy supply chain of the IoT park that do not intersect with the initial node location inside the IoT park, and the devices in the initial node location inside the IoT park that do not intersect do not consume energy, the initial node location inside the IoT park that intersects with the energy supply chain of the IoT park will be set as the energy-consuming node location inside the IoT park based on the intelligent control terminal. It is understandable that the energy-consuming nodes within the IoT park are determined by whether they intersect with the energy supply chain of the IoT park. If they intersect with the energy supply chain of the IoT park, it means that the device has been put into use. If they do not intersect with the energy supply chain of the IoT park, it means that the device is a backup device. Therefore, by obtaining the energy supply chain of the IoT park, the number of nodes can be reduced, which in turn reduces the computational load of the nodes. The node screening module analyzes the locations of energy-consuming nodes within the IoT park using the internal circuit distribution diagram to obtain the actual node locations within the IoT park. The specific steps include: Based on the node filtering module, the internal structure map of the IoT park is marked using energy supply equipment identifiers to determine the location of the energy supply equipment. Based on the node filtering module, location matching is performed on the location of energy supply equipment, the location of energy-consuming nodes within the IoT park, and the energy supply chain route of the IoT park. If all starting points of the energy supply chain in the IoT park are the locations of energy supply equipment, and all ending points of the energy supply chain in the IoT park are the locations of energy-consuming nodes within the IoT park, and the energy consumed by the equipment at the energy-consuming nodes within the IoT park is supplied by the energy supply equipment, then based on the node filtering module, the locations of energy-consuming nodes within the IoT park are set as the actual node locations within the IoT park. If any of the starting points of the energy supply chain path in the IoT park are not the location of the energy supply equipment, the equipment at the energy-consuming node location within the IoT park that is not the location of the energy supply equipment will be set as the load. Based on the node filtering module, the starting point of the energy supply chain path in the IoT park that is the location of the energy supply equipment and all the ending points of the energy supply chain path in the IoT park that are the locations of the energy-consuming nodes within the IoT park will be set as the actual node locations within the IoT park. In this embodiment, to further reduce the computational load, the energy-consuming nodes within the IoT park are further reduced by classifying some nodes as loads. Therefore, the energy-consuming nodes within the IoT park are reduced based on the location of the energy supply equipment and the energy supply chain path of the IoT park. If the starting point of an energy-consuming node is the location of the energy supply equipment, then that node is a real node. If the starting point of an energy-consuming node is the location of another node, then that node is classified as the load of that other node and is no longer treated as a node. Therefore, by reducing the nodes based on the location of the energy supply equipment and the energy supply chain path of the IoT park, the computational load of subsequent nodes is shortened.

[0020] Example 2 The node energy consumption calculation module is used to calculate the load energy consumption of real nodes within the IoT park, and to obtain the initial energy consumption and real-time energy consumption of the real nodes. Specifically, it includes the following steps: Based on intelligent control terminals, information is extracted and processed from the internal structure drawings of the IoT park using the actual node locations within the park as features, to obtain the load data of the actual nodes. Based on the intelligent control terminal, the load data of real nodes is extracted and processed with the characteristic of not performing tasks, so as to obtain the energy consumption of all loads when there are no tasks. Based on the node energy consumption calculation module, the energy consumption of all loads when there are no tasks is summed to obtain the initial energy consumption of the actual node. Based on the node energy consumption calculation module, the load data of real nodes is calculated and processed to obtain the real-time energy consumption of real nodes. Understandably, the initial energy consumption of a real node is obtained by summing the energy consumed by the devices when they were first put into use in the load data of the real node. This is because these devices do not immediately execute tasks when they are first put into use. At this time, the energy consumed by the devices is the energy required to maintain the normal operation of the devices. Therefore, the load data of a real node includes not only the historical operating data of the devices but also the real-time operating data of the devices. The process of calculating the load data of real nodes based on the node energy consumption calculation module to obtain the real-time energy consumption of real nodes includes the following steps: Based on the intelligent control terminal, the load data of real nodes is extracted and processed with the execution of tasks as the feature to obtain the energy consumption of loads that are not executing tasks, the energy consumption of loads that are executing tasks, and the content of the tasks being executed. Based on the node energy consumption calculation module, the energy consumption of the load that is not executing tasks and the energy consumption of the load that is executing tasks are summed to obtain the real-time energy consumption of the actual node. In this embodiment, to determine whether a real node is abnormal, it is necessary to analyze the real node's real-time energy consumption. Therefore, the initial energy consumption of the real node is set as a control group, and the real-time energy consumption of the real node is compared and analyzed to determine whether any equipment is abnormal.

[0021] Example 3 The node energy consumption analysis module is used to compare and analyze the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park. Specifically, it includes the following steps: Based on the intelligent control terminal, the difference between the initial energy consumption and the real-time energy consumption of the real node is calculated to obtain the energy consumption difference when the real node performs the task. Based on the intelligent control terminal, the task content being executed is evaluated and processed to obtain the predicted energy consumption value when the actual node is executing the task. Based on the node energy consumption analysis module, the energy consumption difference of the actual node when performing tasks and the predicted energy consumption of the actual node when performing tasks are compared and analyzed to determine whether there are any abnormal energy consumption locations within the IoT park. The node energy consumption analysis module compares and analyzes the energy consumption difference between actual nodes performing tasks and the predicted energy consumption of actual nodes performing tasks to determine whether there are locations with abnormal energy consumption within the IoT park. Specifically, this includes the following steps: Based on the node energy consumption analysis module, the difference in energy consumption when the actual node performs a task and the predicted value of energy consumption when the actual node performs a task are judged and processed. If the energy consumption difference when the actual node performs a task is approximately equal to the predicted energy consumption when the actual node performs a task, or if the difference between the energy consumption difference when the actual node performs a task and the predicted energy consumption when the actual node performs a task is within 10 percent of the predicted energy consumption when the actual node performs a task, there are no abnormal energy consumption locations within the IoT park. If the difference between the energy consumption of the actual node when performing the task and the predicted energy consumption of the actual node when performing the task is greater than 10 percent of the predicted energy consumption of the actual node when performing the task, there is an abnormal energy consumption location within the IoT park. Based on the node energy consumption analysis module, the abnormal energy consumption location is uploaded to the intelligent control terminal, and the intelligent control terminal sends maintenance information of the abnormal energy consumption location to the electronic equipment of the maintenance personnel. In this embodiment, if the device corresponding to the real node malfunctions, the energy consumed by that device while performing a task will increase. Therefore, the content of the currently executed task is evaluated to obtain the predicted energy consumption value of the real node when performing the task. Then, the difference between the actual energy consumption difference and the predicted energy consumption value of the real node when performing the task is compared to determine whether the device corresponding to the real node is malfunctioning. It is worth noting that as the time the device spends performing the task increases, the device temperature will rise, and its energy consumption will increase. However, this part of the energy consumption is normal. In order to more accurately determine the status of the device corresponding to the real node, this part of the consumption needs to be taken into account. That is, if the difference between the actual energy consumption difference and the predicted energy consumption value of the real node when performing the task is within 10% of the predicted energy consumption value of the real node when performing the task, it means that the device corresponding to the real node is not malfunctioning. If it is higher than this value, it means that the device is malfunctioning.

[0022] Reference Figure 2 As shown, the method for energy consumption monitoring and intelligent control services in IoT parks based on digital twins employs the aforementioned digital twin-based IoT park energy consumption monitoring and intelligent control service system to monitor and intelligently control energy consumption in IoT parks, including: S100. Determine the initial node location within the IoT park. Based on the intelligent control terminal, perform position correction processing on the initial node location within the IoT park through the energy supply chain route of the IoT park to obtain the actual node location within the IoT park. S200: Based on the intelligent control terminal, the load energy consumption calculation of the real node locations within the IoT park is performed to obtain the initial energy consumption and real-time energy consumption of the real nodes. S300, based on the intelligent control terminal, compares and analyzes the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park.

[0023] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A digital twin-based IoT-based park energy consumption monitoring and intelligent control service system, characterized in that, include: The intelligent control terminal is used to control the data transmission and information interaction between various modules. The intelligent control terminal is also used to perform energy consumption calculation and energy consumption comparison of the real node locations within the IoT park to determine whether there are any abnormal energy consumption locations within the IoT park. The database system is used to store the internal structure drawings and internal circuit distribution drawings of the Internet of Things (IoT) park. The node filtering module performs position correction processing on the initial node positions inside the IoT park through the energy supply chain route of the IoT park to obtain the real node positions inside the IoT park. The node energy consumption calculation module is used to perform load energy consumption calculation on the actual node locations within the IoT park to obtain the initial energy consumption and real-time energy consumption of the actual nodes. The node energy consumption analysis module is used to compare and analyze the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park.

2. The IoT-based campus energy consumption monitoring and intelligent control service system based on digital twins as described in claim 1, characterized in that, The node selection module performs position correction processing on the initial node positions within the IoT park through the energy supply chain route of the IoT park to obtain the actual node positions within the IoT park. Specifically, this includes the following steps: Based on the intelligent control terminal, data retrieval and processing are performed on the database system to obtain the internal structure drawings and internal circuit distribution drawings of the IoT park. Based on intelligent control terminals, the devices in the internal structure drawings of the Internet of Things (IoT) park are marked using device identifiers to determine the initial node positions within the IoT park. Based on the intelligent control terminal, the initial node positions inside the IoT park are corrected by using the internal circuit distribution diagram of the IoT park to obtain the actual node positions inside the IoT park.

3. The IoT-based campus energy consumption monitoring and intelligent control service system according to claim 2, characterized in that, The process of obtaining the actual node locations within the IoT park by correcting the initial node locations using the internal circuit distribution diagram of the IoT park based on the intelligent control terminal includes the following steps: Based on intelligent control terminals, information is extracted and processed from the internal circuit distribution diagram of the Internet of Things (IoT) park using circuit wiring characteristics to obtain the energy supply chain route of the IoT park. Based on the intelligent control terminal, the initial node locations within the IoT park are screened through the energy supply chain route of the IoT park to obtain the locations of energy-consuming nodes within the IoT park. Based on the node screening module, the location of energy-consuming nodes inside the IoT park is analyzed by using the internal circuit distribution diagram of the IoT park to obtain the actual node locations inside the IoT park.

4. The IoT-based campus energy consumption monitoring and intelligent control service system based on digital twins according to claim 3, characterized in that, The process of obtaining the locations of energy-consuming nodes within the IoT park by filtering initial node locations through the energy supply chain path of the IoT park based on intelligent control terminals includes the following steps: Based on the intelligent control terminal, the energy supply chain route of the Internet of Things (IoT) park performs location matching processing on the initial node locations within the IoT park. If the energy supply chain of the IoT park intersects with all the initial node locations within the IoT park, and all the devices at the initial node locations within the IoT park require energy consumption, then based on the intelligent control terminal, the initial node locations within the IoT park will be set as the energy-consuming node locations within the IoT park. If there are nodes in the energy supply chain of the IoT park that do not intersect with the initial node location within the IoT park, and the devices at the initial node location within the IoT park that do not intersect do not consume energy, then based on the intelligent control terminal, the initial node location within the IoT park that intersects with the energy supply chain of the IoT park will be set as the energy-consuming node location within the IoT park.

5. The IoT-based campus energy consumption monitoring and intelligent control service system according to claim 4, characterized in that, The node-based filtering module analyzes the locations of energy-consuming nodes within the IoT park using the internal circuit distribution diagram of the IoT park to obtain the actual node locations within the IoT park. Specifically, this includes the following steps: Based on the node filtering module, the internal structure map of the IoT park is marked using energy supply equipment identifiers to determine the location of the energy supply equipment. Based on the node filtering module, location matching is performed on the location of energy supply equipment, the location of energy-consuming nodes within the IoT park, and the energy supply chain route of the IoT park. If all starting points of the energy supply chain in the IoT park are the locations of energy supply equipment, and all ending points of the energy supply chain in the IoT park are the locations of energy-consuming nodes within the IoT park, and the energy consumed by the equipment at the energy-consuming nodes within the IoT park is supplied by the energy supply equipment, then based on the node filtering module, the locations of energy-consuming nodes within the IoT park are set as the actual node locations within the IoT park. If any of the starting points of the energy supply chain path in the IoT park are not located at the location of an energy supply device, then the device at the energy-consuming node location within the IoT park that is not located at the location of an energy supply device will be set as a load. Based on the node filtering module, the starting point of the energy supply chain path in the IoT park that is located at the location of an energy supply device, and all the ending points of the energy supply chain path in the IoT park that are energy-consuming nodes within the IoT park, will be set as the actual node locations within the IoT park.

6. The IoT-based campus energy consumption monitoring and intelligent control service system based on digital twins according to claim 1, characterized in that, The node energy consumption calculation module is used to perform load energy consumption calculation on the actual node locations within the IoT park, and to obtain the initial energy consumption and real-time energy consumption of the actual nodes. Specifically, it includes the following steps: Based on intelligent control terminals, information is extracted and processed from the internal structure drawings of the IoT park using the actual node locations within the park as features, to obtain the load data of the actual nodes. Based on the intelligent control terminal, the load data of real nodes is extracted and processed with the characteristic of not performing tasks, so as to obtain the energy consumption of all loads when there are no tasks. Based on the node energy consumption calculation module, the energy consumption of all loads when there are no tasks is summed to obtain the initial energy consumption of the actual node. Based on the node energy consumption calculation module, the load data of real nodes is calculated and processed to obtain the real-time energy consumption of real nodes.

7. The IoT-based campus energy consumption monitoring and intelligent control service system according to claim 6, characterized in that, The node-based energy consumption calculation module processes the load data of real nodes to obtain the real-time energy consumption of real nodes, specifically including the following steps: Based on the intelligent control terminal, the load data of real nodes is extracted and processed with the execution of tasks as the feature to obtain the energy consumption of loads that are not executing tasks, the energy consumption of loads that are executing tasks, and the content of the tasks being executed. Based on the node energy consumption calculation module, the energy consumption of the load that is not performing a task and the energy consumption of the load that is performing a task are summed to obtain the real-time energy consumption of the actual node.

8. The IoT-based campus energy consumption monitoring and intelligent control service system according to claim 1, characterized in that, The node energy consumption analysis module is used to compare and analyze the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park. Specifically, it includes the following steps: Based on the intelligent control terminal, the difference between the initial energy consumption and the real-time energy consumption of the real node is calculated to obtain the energy consumption difference when the real node performs the task. Based on the intelligent control terminal, the task content being executed is evaluated and processed to obtain the predicted energy consumption value when the actual node is executing the task. Based on the node energy consumption analysis module, the difference in energy consumption when the actual node performs a task and the predicted energy consumption when the actual node performs a task are compared and analyzed to determine whether there are any abnormal energy consumption locations within the IoT park.

9. The IoT-based campus energy consumption monitoring and intelligent control service system according to claim 8, characterized in that, The node-based energy consumption analysis module compares and analyzes the energy consumption difference between actual nodes performing tasks and the predicted energy consumption of actual nodes performing tasks to determine whether there are any locations with abnormal energy consumption within the IoT park. Specifically, this includes the following steps: Based on the node energy consumption analysis module, the difference in energy consumption when the actual node performs a task and the predicted value of energy consumption when the actual node performs a task are judged and processed. If the energy consumption difference when the actual node performs a task is approximately equal to the predicted energy consumption when the actual node performs a task, or if the difference between the energy consumption difference when the actual node performs a task and the predicted energy consumption when the actual node performs a task is within 10 percent of the predicted energy consumption when the actual node performs a task, there are no abnormal energy consumption locations within the IoT park. If the difference between the energy consumption of the actual node performing the task and the predicted energy consumption of the actual node performing the task is greater than 10% of the predicted energy consumption of the actual node performing the task, there is an abnormal energy consumption location within the IoT park. Based on the node energy consumption analysis module, the abnormal energy consumption location is uploaded to the intelligent control terminal, and the intelligent control terminal sends maintenance information of the abnormal energy consumption location to the electronic equipment of the maintenance personnel.

10. A method for energy consumption monitoring and intelligent control services in IoT parks based on digital twins, comprising using the IoT park energy consumption monitoring and intelligent control service system based on digital twins as described in any one of claims 1-9 to perform energy consumption monitoring and intelligent control in IoT parks, including: S100. Determine the initial node location within the IoT park. Based on the intelligent control terminal, perform position correction processing on the initial node location within the IoT park through the energy supply chain route of the IoT park to obtain the actual node location within the IoT park. S200: Based on the intelligent control terminal, the load energy consumption calculation of the real node locations within the IoT park is performed to obtain the initial energy consumption and real-time energy consumption of the real nodes. S300, based on the intelligent control terminal, compares and analyzes the initial energy consumption and real-time energy consumption of real nodes to determine whether there are any abnormal energy consumption locations within the IoT park.

Images