A park carbon emission real-time monitoring and early warning system based on an internet of things

Abstract

This invention discloses an IoT-based real-time carbon emission monitoring and early warning system for industrial parks, relating to the field of carbon emission regulation technology. It includes: a configuration module for dividing the industrial park into a multi-scale spatial grid, identifying all carbon-emitting devices within the grid, configuring a monitoring point for each device, and configuring a control center for all monitoring points, wherein the control center has multiple control points; a calculation module for calculating the total carbon emissions of the industrial park for each preset time period based on the multi-scale spatial grid; and an early warning module for determining the difference between the target total carbon emissions and the total carbon emissions, and judging whether the difference is less than a preset early warning threshold. This invention automatically implements emission reduction control operations by linking monitoring groups to specific locations, and automatically disbands the monitoring group after control is completed, reducing the occupation of cloud platform resources.

Description

Technical Field

[0001] This invention relates to the field of carbon emission monitoring technology, specifically to an Internet of Things-based real-time carbon emission monitoring and early warning system for industrial parks. Background Technology

[0002] With the increasing severity of global climate change and the deepening implementation of the "dual carbon" target, carbon emission management in various industrial parks, as concentrated carbon emission areas, has become a focus of attention for all sectors of society. These parks typically house a large number of production enterprises, office buildings, and supporting facilities, with diverse equipment, complex energy consumption structures, and dispersed carbon emission sources, posing significant challenges to real-time monitoring and effective control of carbon emissions. When carbon emission exceedance alarms occur, manual judgment is often required to determine which equipment can be shut down, how much can be shut down, and for how long. This decision-making process is inefficient, highly dependent on experience, and difficult to automate in responding to emission exceedance events.

[0003] Therefore, how to achieve real-time perception of the importance of equipment in the park and dynamically match emission reduction pressure (carbon emission reduction) to realize automatic emission reduction of various equipment in the park is an urgent technical problem to be solved.

[0004] In view of this, the present invention proposes an Internet of Things-based real-time monitoring and early warning system for carbon emissions in industrial parks to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide an Internet of Things-based real-time monitoring and early warning system for carbon emissions in industrial parks, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a real-time monitoring and early warning system for carbon emissions in industrial parks based on the Internet of Things, comprising: The configuration module is used to divide the park into grids to obtain a multi-scale spatial grid, identify all devices with carbon emissions within the multi-scale spatial grid, configure a monitoring point for each device, configure a control center for all monitoring points, and the control center is configured with multiple control points. The accounting module is used to calculate the total carbon emissions of the park for each preset time period based on a multi-scale spatial grid. The early warning module is used to determine the difference between the target total carbon emissions and the total carbon emissions, and to determine whether the difference is less than the preset early warning threshold. The control module is used to freely group multiple monitoring points based on preset site clusters when the difference is less than the warning threshold, to obtain site-connected monitoring clusters, and to control carbon emissions based on site-connected monitoring clusters until the difference is greater than or equal to the warning threshold. The visualization module is used to display multi-scale spatial grids and monitoring points.

[0007] In a preferred embodiment, the configuration module includes: A dividing unit is used to divide the park into grids to obtain a multi-scale spatial grid, wherein the multi-scale spatial grid includes a first-level grid, a second-level grid, and a third-level grid; The determination unit is used to determine the carbon source classification system of the park, and based on the carbon source classification system, to determine all equipment in the park that emits carbon. A configuration unit is used to configure a monitoring point for each device in the three-level grid on a one-to-one basis, wherein the monitoring point is bound to the device number configured therewith, and a monitoring point number is configured for each monitoring point; The control unit is used to configure a control center for all monitoring points. The control center corresponds to multiple control points. Each control point is connected to a device and the multiple control points are connected to all monitoring points in a one-to-one correspondence. The control center is deployed on a cloud platform.

[0008] In a preferred embodiment, the accounting module includes: The calculation unit is used to calculate the real-time carbon emissions of the park for each preset time period using a multi-scale spatial grid, and obtain the total carbon emissions of the park.

[0009] In a preferred embodiment, the early warning module includes: The preset unit is used to determine the target total carbon emissions for each preset time period within the park and to preset the early warning threshold. The early warning unit is used to obtain the difference between the target total carbon emissions and the total carbon emissions, and to determine whether the difference is less than the preset early warning threshold.

[0010] In a preferred embodiment, the control module includes: The clustering unit is used to set clustering trigger conditions and, based on the clustering trigger conditions, to freely cluster multiple monitoring points according to preset site clusters; The control unit is used to control carbon emissions from monitoring sites based on free association, and to disband the monitoring group linked to the sites after the carbon emission control is completed.

[0011] In a preferred embodiment, the clustering unit includes: The setting unit is used to set multiple receptor points for each monitoring point. The multiple receptor points correspond to the real-time status of the monitoring point. The receptor points are exposed according to the real-time status of the monitoring point. The real-time status and the receptor points include extremely high level, high level, medium level and low level. The multiple real-time statuses correspond one-to-one with the multiple receptor points. Each receptor point is bound to the carbon emission code of the corresponding monitoring point. The carbon emission code of the monitoring point is obtained by mapping the carbon emission of the monitoring point through a mapping table. The allocation unit is used to set up multiple sites corresponding to the control center and allocate the differences to obtain multiple individual differences. Each site is bound to a corresponding individual difference code, and the individual difference code is obtained by mapping the individual differences through a mapping table. The linker unit is used to link multiple sites one-to-one based on multiple monomer differences to form a site cluster, and to use the sites on the site cluster to bind with the exposed receptor sites on the monitoring point to obtain the site-linked monitoring cluster.

[0012] In a preferred embodiment, the step of allocating the differences to obtain multiple individual differences includes: All monitoring points exposed to low-level receptors were screened to form a primary candidate set. The number of monitoring points with the same carbon emissions in the candidate set was counted. Monitoring points with the same carbon emissions were grouped into the same monitoring point group and sorted in descending order of the number of monitoring points in each group. Starting with the group of monitoring points with the largest number, priority is given to selecting monitoring points within the group that expose low-level receptors. Monitoring points within the group are selected sequentially until the sum of the carbon emissions of all selected monitoring points equals the difference. The carbon emissions corresponding to each selected monitoring point are considered as a single-unit difference. This process is repeated to obtain multiple single-unit differences. If the carbon emissions of monitoring points in the primary candidate set are less than the difference, monitoring points exposed to medium-level receptors are used for supplementary screening. This process is repeated until the sum of the carbon emissions of all selected monitoring points equals the difference.

[0013] In a preferred embodiment, the step of connecting multiple sites based on one-to-one labeling of multiple monomer differences to form a site cluster, and using the sites on the site cluster to bind with the exposed receptor sites on the monitoring points to obtain the site-linked monitoring cluster includes: Multiple sites within the control center with the same numerical value as the monomer difference are labeled one-to-one based on multiple monomer differences, and the labeled sites are connected to obtain site clusters; Multiple sites on the site cluster are connected to the carbon emission codes of the exposed receptor sites on multiple monitoring points through their own bound monomer difference codes. After connection, the multiple sites on the site cluster carry the carbon emission codes of the receptor sites they are connected to, thus obtaining the site-linked monitoring cluster.

[0014] In a preferred embodiment, the control unit includes: An execution unit is used to perform carbon emission control on the control points corresponding to the site-linked monitoring group, wherein the carbon emission control includes performing control operations on the control points corresponding to the site-linked monitoring group; The disbanding unit is used to determine that carbon emission control has been completed when the difference after control is greater than or equal to the warning threshold, and to disband the site-linked monitoring group.

[0015] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention obtains site clusters by corresponding difference marker sites, automatically achieving precise matching between emission reduction pressure and shutdown equipment, avoiding the impact of a one-size-fits-all shutdown on core production equipment, and achieving the optimal balance between carbon emission control and production continuity. 2. This invention combines the sites on the site cluster with the exposed receptor points on the monitoring points to obtain the site-linked monitoring cluster. By controlling the site-linked monitoring cluster, carbon emission reduction can be implemented on the equipment corresponding to the monitoring points within the site-linked monitoring cluster. After the control is completed, the cluster is automatically disbanded, which can reduce the occupation of operating resources in the cloud platform. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0017] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1, please refer to Figure 1 As shown in this embodiment, a real-time monitoring and early warning system for carbon emissions in a park based on the Internet of Things includes: The configuration module is used to divide the park into grids to obtain a multi-scale spatial grid, identify all devices with carbon emissions within the multi-scale spatial grid, configure a monitoring point for each device, configure a control center for all monitoring points, and the control center is configured with multiple control points. The accounting module is used to calculate the total carbon emissions of the park for each preset time period based on a multi-scale spatial grid. The early warning module is used to determine the difference between the target total carbon emissions and the total carbon emissions, and to determine whether the difference is less than the preset early warning threshold. The control module is used to freely group multiple monitoring points based on preset site clusters when the difference is less than the warning threshold, to obtain site-connected monitoring clusters, and to control carbon emissions based on site-connected monitoring clusters until the difference is greater than or equal to the warning threshold. The visualization module is used to display multi-scale spatial grids and monitoring points. The visualization module includes visualization units, which are used to display multi-scale spatial grids and monitoring points, and synchronously update and display the monitoring points under control (site-linked monitoring groups) on the multi-scale spatial grid.

[0020] In one embodiment, the configuration module includes: A dividing unit is used to divide the park into grids to obtain a multi-scale spatial grid, wherein the multi-scale spatial grid includes a first-level grid, a second-level grid, and a third-level grid; The determination unit is used to determine the carbon source classification system of the park, and based on the carbon source classification system, to determine all equipment in the park that emits carbon. A configuration unit is used to configure a monitoring point for each device in the three-level grid on a one-to-one basis, wherein the monitoring point is bound to the device number configured therewith, and a monitoring point number is configured for each monitoring point; The control unit is used to configure a control center for all monitoring points. The control center corresponds to multiple control points. Each control point is connected to a device and the multiple control points are connected to all monitoring points in a one-to-one correspondence. The control center is deployed on a cloud platform.

[0021] It should be noted that the division of units uses the preset BeiDou spatial coordinate system as the basic spatial reference to determine the spatial geographic coordinate system of the park, establish a unified latitude, longitude, elevation, and plane projection reference, and ensure the consistency of spatial positioning across multiple scales. Simultaneously, grid coding rules are formulated, using a combination of numbers and letters to uniquely identify the first, second, and third-level grids. The coding information includes the grid level, geographic region, and sequence number attribute. The multi-scale spatial grid is divided into three nested grids based on the park's area, functional zones, carbon emission density, and management requirements. The first-level grid forms a macro-level regular grid covering the entire park, used for total carbon emission statistics. The second-level grid is based on the park's functional zones, using a combination of regular and irregular grids to match the boundaries of different functional areas. This system enables differentiated carbon emission accounting across different regions. The three-level grid uses the equipment deployment area as the smallest granularity and employs the BeiDou standard grid for fine-grained division, ensuring that each carbon emission device can be completely assigned to a unique three-level grid. This achieves accurate grid placement and traceability of carbon emission data, allowing multiple devices to be deployed within a single three-level grid area. Boundary verification and topology correction are performed on the completed multi-scale spatial grid to eliminate grid overlaps, gaps, and misalignments. Grid boundary matching and calibration are performed using a real-world map of the park, building layout diagrams, and equipment layout diagrams to ensure a high degree of consistency between the grid and the actual physical space. Simultaneously, grid division parameters, boundary coordinates, and hierarchical relationships (hierarchical mapping relationships between first-level, second-level, and third-level grids) are recorded, forming a grid division archive which is synchronized to the cloud platform database, thus obtaining the multi-scale spatial grid. The determination of the unit is based on the compilation of the urban greenhouse gas emission inventory, and is summarized and classified during the data collection and accounting process to determine the carbon source classification system. In the carbon source classification system, the carbon source is the activity / sector that generates greenhouse gas emissions (such as coal-fired power plants, vehicle exhaust, and industrial processes). Based on the carbon source, all equipment in the park that emits carbon is determined, such as production equipment, transportation equipment, lighting equipment, etc. in the park. Here, equipment is a general term for objects in the park that emit carbon. The configuration unit configures a monitoring point for each device in the three-level grid on a one-to-one basis, and assigns a number to the monitoring point and binds it to the device number configured on the monitoring point. This achieves the binding between the monitoring point and the device. The monitoring point number and the device number are unique. The control unit configures a control center for all monitoring points. The control center, through its corresponding (configured) multiple control points, can control all monitoring points. The control point is essentially the operation switch of the equipment mapped to the monitoring point in the cloud platform (such as the power switch of production equipment, the power switch of lighting equipment, the start switch of transportation equipment, and any switch that can turn the equipment carbon emissions on or off). The monitoring point is essentially a virtual machine or virtual carrier, which is a sensor device / equipment itself mapped in the cloud platform and monitors the equipment (some devices can monitor their own operating status). The control center is essentially the convergence point of all monitoring points in the carbon accounting spatiotemporal cloud platform and also the origin of control commands.

[0022] In one embodiment, the accounting module includes: The calculation unit is used to calculate the real-time carbon emissions of the park for each preset time period using a multi-scale spatial grid, and obtain the total carbon emissions of the park.

[0023] It should be noted that the accounting unit, by determining the carbon source classification system and methodology, matching the park's carbon emission accounting standards, determining the granularity of the accounting period, loading the spatial gridded data database construction specifications and point-line-surface coding benchmarks, establishes a one-to-one correspondence between the three-level grid and monitoring points, equipment, and carbon emission data, and clarifies the accounting data caliber, measurement units, and data validity judgment rules; taking the equipment within the three-level grid as the smallest accounting unit, it collects real-time equipment operation data transmitted from the corresponding monitoring points, and adopts bottom-up accounting methods such as electricity consumption method, fuel consumption method, and power method, substituting them into preset carbon emission accounting factors and multi-parameter accounting analysis models, to calculate the carbon emissions of a single device and a single three-level grid in real time, forming a fine-grained local-level grid carbon emission accounting result; the three-level grid accounting results are summarized from bottom to top according to the grid hierarchy to obtain the carbon emissions of the second-level grid and the first-level grid, and so on. By combining macroscopic remote sensing data and spatial interpolation algorithms, a top-down accounting approach is used to verify the total carbon emissions of the park, achieving cross-validation of the two-way accounting results and ensuring the accuracy of the total carbon emissions. Multi-scale accounting data is cleaned, deduplicated, and outlier removed, and data formats and statistical standards are standardized. Top-down macroscopic accounting data and bottom-up microscopic monitoring accounting data are matched and integrated at the corresponding grid levels to determine data fusion rules, eliminate accounting biases, and output a unified and valid total carbon emissions figure for each preset time period, which is simultaneously pushed to the early warning and visualization modules. Carbon emission accounting data, accounting time, accounting methods, and accounting model parameters are recorded in real time at each grid level, monitoring point, and device, forming a traceable and verifiable carbon emission accounting ledger, which is simultaneously stored on the cloud platform to provide data support for subsequent carbon emission management review.

[0024] In one embodiment, the early warning module includes: The preset unit is used to determine the target total carbon emissions for each preset time period within the park and to preset the early warning threshold. The early warning unit is used to obtain the difference between the target total carbon emissions and the total carbon emissions, and to determine whether the difference is less than the preset early warning threshold.

[0025] It should be noted that the preset unit determines the target total carbon emissions for each preset time period (e.g., the total emissions allowed this month or this week) based on the park's production plan, emission reduction commitments, or policy requirements. A warning threshold is preset based on this target total carbon emissions (the warning threshold is generally set to 0). The difference between the target total carbon emissions and the total carbon emissions is calculated as follows: if the difference is greater than or equal to 0, no control is required; if the difference is less than 0 (the warning threshold), control is required. For example, if the target total carbon emissions are 1000 kg and the total carbon emissions are 900 kg, then 1000 kg - 900 kg = 100 kg, i.e., the difference... If the value is 100kg and the difference is greater than 0, it means that the total carbon emissions have not exceeded the target total carbon emissions, and there is no need to call the control module. If the total carbon emissions are 1100kg, 1000kg-1100kg=-100kg, that is, the difference is -100kg. The difference is less than 0, which means that the total carbon emissions have exceeded the target total carbon emissions. Based on this, the early warning unit sends an early warning to the subsequent control module to control the difference until the difference is less than or equal to 0kg. Then, by comparing the difference with the early warning threshold, the early warning module can determine whether the total carbon emissions have exceeded the standard, and can realize the park's early warning of carbon emissions exceeding the standard.

[0026] In one embodiment, the control module includes: The clustering unit is used to set clustering trigger conditions and, based on the clustering trigger conditions, to freely cluster multiple monitoring points according to preset site clusters; The control unit is used to control carbon emissions from monitoring sites based on free association, and to disband the monitoring group linked to the sites after the carbon emission control is completed.

[0027] In one embodiment, the clustering unit includes: The setting unit is used to set multiple receptor points for each monitoring point. The multiple receptor points correspond to the real-time status of the monitoring point. The receptor points are exposed according to the real-time status of the monitoring point. The real-time status and the receptor points include extremely high level, high level, medium level and low level. The multiple real-time statuses correspond one-to-one with the multiple receptor points. Each receptor point is bound to the carbon emission code of the corresponding monitoring point. The carbon emission code of the monitoring point is obtained by mapping the carbon emission of the monitoring point through a mapping table. The allocation unit is used to set up multiple sites corresponding to the control center and allocate the differences to obtain multiple individual differences. Each site is bound to a corresponding individual difference code, and the individual difference code is obtained by mapping the individual differences through a mapping table. The linker unit is used to link multiple sites one-to-one based on multiple monomer differences to form a site cluster, and to use the sites on the site cluster to bind with the exposed receptor sites on the monitoring point to obtain the site-linked monitoring cluster.

[0028] In one embodiment, the step of allocating the differences to obtain multiple individual differences includes: All monitoring points exposed to low-level receptors were screened to form a primary candidate set. The number of monitoring points with the same carbon emissions in the candidate set was counted. Monitoring points with the same carbon emissions were grouped into the same monitoring point group and sorted in descending order of the number of monitoring points in each group. Starting with the group of monitoring points with the largest number, priority is given to selecting monitoring points within the group that expose low-level receptors. Monitoring points within the group are selected sequentially until the sum of the carbon emissions of all selected monitoring points equals the difference. The carbon emissions corresponding to each selected monitoring point are considered as a single-unit difference. This process is repeated to obtain multiple single-unit differences. If the carbon emissions of monitoring points in the primary candidate set are less than the difference, monitoring points exposed to medium-level receptors are used for supplementary screening. This process is repeated until the sum of the carbon emissions of all selected monitoring points equals the difference.

[0029] In one embodiment, the step of connecting multiple sites based on one-to-one labeling of multiple monomer differences to form a site cluster, and using the sites on the site cluster to bind with the exposed receptor sites on the monitoring points to obtain the site-linked monitoring cluster includes: Multiple sites within the control center with the same numerical value as the monomer difference are labeled one-to-one based on multiple monomer differences, and the labeled sites are connected to obtain site clusters; Multiple sites on the site cluster are connected to the carbon emission codes of the exposed receptor sites on multiple monitoring points through their own bound monomer difference codes. After connection, the multiple sites on the site cluster carry the carbon emission codes of the receptor sites they are connected to, thus obtaining the site-linked monitoring cluster.

[0030] It should be noted that in the clustering unit, the difference between the target total carbon emissions and the total carbon emissions is less than the warning threshold as the clustering trigger condition. Once the clustering trigger condition is met, the monitoring points are freely clustered using site clusters. Multiple receptor points are set for each monitoring point (each monitoring point corresponds to one device), and each receptor point is bound to the carbon emission code of that monitoring point (including device ID and carbon emission data). Each receptor point represents a real-time state (the number of receptor points is the same for the number of real-time states). Each monitoring point exposes the corresponding receptor point according to its real-time state (real-time states include extremely high level, high level, medium level, and low level; for example, extremely high-level devices expose receptor point R4, high-level devices expose receptor point R4, and so on). Point R3 is the exposure receptor point for medium-level equipment, R2 is the exposure receptor point for low-level equipment, and R1 is the exposure receptor point for low-level equipment. The higher the real-time status of the exposed receptor point, the more "difficult" the equipment is to be shut down; the lower the real-time status of the exposed receptor point, the more "prioritized" the equipment can be shut down. The real-time status is determined based on the number of associated devices of the equipment corresponding to the monitoring point, whether the associated devices are in operation, and the importance of the equipment itself. The more associated devices, the more the equipment is in the working area and is operating normally, and the higher the importance of the equipment, the higher the corresponding real-time status and the higher the exposure level of the corresponding receptor point. The fewer associated devices, the less the equipment is in the non-working area or not operating, and the lower the importance of the equipment, the lower the corresponding real-time status and the lower the exposure level of the corresponding receptor point. The real-time status is calculated as follows: The real-time status is obtained by multiplying the associated equipment quantity coefficient (e.g., if equipment A on the production line shuts down, causing equipment B to also malfunction, equipment B is an associated equipment of equipment A), the operational status coefficient, and the importance coefficient. When there are no associated equipment, the equipment is not operating, or it is a non-operational area such as air conditioning or lighting, the corresponding coefficient value is lower, and the real-time status is lower. When there are many associated equipment, the equipment is operating, or it is equipment in an operational or important area, the corresponding coefficient value is higher, and the real-time status is higher. For example, real-time status S = associated equipment quantity coefficient A × operational status coefficient B × importance coefficient C, where: associated equipment quantity coefficient A, operational status coefficient B, importance coefficient C, and importance coefficient C. Unrelated equipment: A=1, 1-2 related equipment: A=2, ≥3 related equipment: A=3; Operation status coefficient B, equipment in operation: B=2, equipment not in operation: B=1; Importance coefficient C, important equipment (core equipment in production or operation areas, etc.): C=3, general equipment (ordinary auxiliary equipment): C=2, non-important equipment (lighting, air conditioning, idle equipment in non-operation areas): C=1; The final level rule is that the larger the calculated S, the higher the real-time status, and the higher the receptor point exposure level; The level classification rule is: S≥12: extremely high level, 8≤S<12: high level, 4≤S<8: medium level, S<4: low level.

[0031] In the allocation unit, multiple sites are set up corresponding to the control center. Each site is assigned a different integer value, and the same integer value can correspond to multiple sites. The difference values ​​are then allocated to obtain multiple individual difference values. At the control center, sites with the same individual difference values ​​are marked one-to-one (e.g., if the individual difference value is 5, the integer value of the site is also 5, so the site can be marked). Each individual difference value corresponds to one site. The control center distributes the same identifier to the receiving ports of the marked sites. Multiple sites are connected based on the same identifier (i.e., sites are connected end to end in sequence to form a ring network (each site is connected to two adjacent sites), forming a site cluster). For example, wwqrrr is distributed as the identifier for sites 1, 2, and 3 respectively, and the receiving ports of sites 1, 2, and 3 are connected based on the same identifier. The steps for obtaining multiple individual differences are as follows: Using the differences as the total emission reduction, firstly, all monitoring points exposing low-level real-time states are selected to form a candidate set. These monitoring points correspond to equipment with low importance and can be prioritized for shutdown and emission reduction. Next, the real-time carbon emissions of each monitoring point within the candidate set are calculated. Monitoring points with the same carbon emission values ​​are grouped into the same monitoring point group, and sorted in descending order according to the number of monitoring points in each group. Priority is given to emission specifications with a high proportion of equipment to improve allocation efficiency (facilitating the search for other monitoring points with the same real-time state if the equipment corresponding to a monitoring point cannot reduce emissions due to unexpected operation or other events, so that this monitoring point can be combined with the site through a secondary port). Starting from the monitoring point group with the largest number of monitoring points, monitoring points are selected sequentially, and the total emissions are accumulated. The carbon emissions of selected monitoring points are counted until the sum equals the difference to be allocated. The carbon emissions corresponding to each selected monitoring point are considered as a single difference. All single differences are combined to form an emission reduction allocation scheme that matches the total difference, thereby completing the allocation of the difference to multiple single differences. If the carbon emissions of monitoring points in the primary candidate set are less than the difference, monitoring points exposed to medium-level receptor points are selected for supplementary screening, and so on, until the sum of the carbon emissions of all selected monitoring points equals the difference. During the screening process, a strict priority order from low to high level is followed, that is, monitoring points exposed to low-level receptor points are locked first, and then medium-level, high-level, and very high-level are screened in sequence to ensure that emission reduction regulation is preferentially applied to the equipment with the lowest priority and the least impact on production. Each site in the site cluster is connected to the carbon emission code of the monitoring point corresponding to the exposed low-level receptor site through its differential code. Here, connection means that the same differential code finds the same carbon emission code. After the connection is successful, the site carries the monitoring point, thereby realizing the site cluster and the site-carried (connected) monitoring point to freely cluster together, resulting in a site-linked monitoring cluster. Specifically: The receptor point is essentially a virtual machine's connection port; exposing it means making it available from a hidden state. The site is essentially a virtual machine, with each site having three ports: a receiving port, a main port, and a secondary port. Each site connects to other sites within a site cluster via the main port. The marked site is essentially a site selected and locked by the control center from a preset pool of sites based on the monomer difference value. Sites with values ​​exactly matching the monomer difference value are assigned a unified connection identifier, qualifying them to participate in forming site clusters and matching with corresponding receptor points. The connection between sites and receptor points is essentially based on coded logical address matching. Each site is bound to a monomer difference code, and each receptor point is bound to a carbon emission code (i.e., the code corresponding to the carbon emission per unit time, which can be 10 minutes, 2 seconds, etc.). (0 minutes, etc., both the individual unit difference code and the carbon emission code are generated by converting the corresponding carbon emission values ​​through the same mapping table). In the control center, the two are used as logical addresses or identification tags. When the receiver point is in an exposed state (such as the corresponding low-level real-time operation state), it will actively report a status signal to the control center. The signal content includes the equipment identification, level information and its emission reduction value. The routing engine of the control center performs matching according to preset rules: if the individual unit difference code of a certain site is the same as the carbon emission code of a certain receiver point, the two are connected. After the matching is successful, the routing engine logically points the pointer of the site to the corresponding receiver point, completing the logical connection between the site and the receiver point. The free grouping is essentially a dynamic scheduling method that automatically combines suitable monitoring points into temporary control groups based on the matching relationship between the site and the receiver point. Furthermore, the control module obtains site clusters through corresponding difference marker sites, automatically achieving precise matching between emission reduction pressure and shutdown equipment. This ensures that more important equipment is less likely to be included in the shutdown scope, while less important equipment is given priority in emission reduction tasks. This avoids the impact of a one-size-fits-all shutdown on core production equipment, achieving an optimal balance between carbon emission control and production continuity. By combining sites on the site clusters with exposed receptor points on the monitoring points, site-connected monitoring clusters can be obtained. By controlling the site-connected monitoring clusters, carbon emission reductions can be implemented for the equipment corresponding to the monitoring points within the site-connected monitoring clusters. The clusters are automatically disbanded after control is completed, reducing the occupation of operating resources within the cloud platform.

[0032] Furthermore, it should be noted that the three ports on the site serve the following functions: a receiving port, used to receive the identifier from the control center and connect with other marked sites; a main port, used to connect with monitoring points; and a secondary port, which is essentially a secondary main port. When the real-time status of the monitoring point corresponding to the receptor point connected to the site changes, the secondary port on the site connects with the receptor points (exposed receptor points) of other monitoring points within the same monitoring point group. When both the main port and the secondary port of the site are connected to monitoring points, a dynamic equilibrium is formed between the monitoring point whose real-time status has changed and other monitoring points. This dynamic equilibrium is characterized by the monitoring point whose real-time status has changed gradually increasing the carbon emissions generated by its corresponding equipment. Other monitoring points gradually reduce their corresponding carbon emission settings. The carbon emission increase at a monitoring point whose real-time status changes equals the carbon emission decrease at other monitoring points, reaching a dynamic equilibrium. This continues until the monitoring point whose real-time status changed fully increases its carbon emissions to normal levels, while other monitoring points fully reduce their corresponding carbon emissions. The gradual increase and decrease of monitoring points are based on changes in the equipment adjustment parameters of the corresponding devices. When establishing dynamic equilibrium, multiple equipment adjustment parameters and multiple carbon emission parameter mapping tables are set for each device. Specifically, the essence of dynamic equilibrium is: establishing a connection between the main port and the sub-port of the monitoring point to obtain... A transition line is formed by sequentially setting up multiple carriers (which transmit instructions on the equipment adjustment parameters to the corresponding control points via monitoring points). Each carrier separately divides and carries the carbon emission amount (i.e., the carbon emission amount corresponding to the activation of equipment at the monitoring point whose real-time status has changed; for example, activating equipment A increases carbon emissions by 3 kg). These carriers then adjust the corresponding equipment adjustment parameters at the monitoring point whose real-time status has changed until the adjustment parameters for all carriers are complete. This process gradually transfers carbon emissions from the monitoring point whose real-time status has changed to other monitoring points. The essence of the transition line is... It is a virtual logical channel connecting the main port and the secondary port. It represents the carbon emission transfer path from the original monitoring point to the substitute monitoring point. It is an ordered, time-sequential data transmission or state transition pipeline used to carry and manage the intermediate states in the entire transfer process. The carrier is essentially a virtual data packet or task unit running on the transition line. Each carrier carries a small increment (the carbon emission after being divided) and carries the corresponding equipment adjustment parameter adjustment instructions. The carrier moves from the main port to the secondary port along the transition line, representing the process of carbon emissions gradually transferring from the original equipment to the substitute equipment. The movement of the carrier (it can move to the secondary port after executing the corresponding equipment adjustment parameters) and the adjustment achieve a gradual and smooth transition.For example, monitoring point A (the monitoring point whose real-time status changes) is connected to the main port of the site, and monitoring point B (corresponding to other monitoring points mentioned earlier) is connected to the secondary port of the site. There is a transition line between the main port and the secondary port, and multiple carriers are set sequentially on the transition line. The equipment corresponding to monitoring point A needs to increase its carbon emissions from 0 kg to 3 kg, and the equipment corresponding to monitoring point B needs to decrease its carbon emissions from 3 kg to 0 kg. The 3 kg is divided (it can be divided according to the carbon emissions in the parameter mapping table, prioritizing the smaller carbon emissions and then gradually increasing the larger carbon emissions), resulting in 3 carriers, each carrier... For a carbon emission of 1 kg, during the dynamic balancing process, if the carbon emission of the equipment corresponding to monitoring point A increases by 1 kg, the carbon emission of the equipment corresponding to monitoring point B decreases by 1 kg. When the carbon emission of the corresponding equipment at monitoring points A and B increases or decreases, monitoring points A and B respectively select the corresponding equipment adjustment parameters through their corresponding equipment parameter mapping table to achieve the increase or decrease of carbon emission of the corresponding equipment at monitoring points A and B. The parameter mapping table can be represented as: 1 kg (carbon emission) → 200 Hz (output power, i.e., equipment adjustment parameter), 2 kg (carbon emission) → 400 Hz (output power, i.e., equipment adjustment parameter), etc. After reaching dynamic equilibrium, the secondary port fully establishes connections with other monitoring points, allowing the primary port to disconnect from monitoring points whose real-time status has changed. This enables the carbon emissions corresponding to the changed monitoring points to be reduced through other monitoring points connected to the secondary port, achieving automatic switching of monitoring points with changing real-time status. This makes the entire system more stable, ensures a smooth handover, and prevents drastic changes in the equipment at other monitoring points (e.g., no need for emergency shutdown) and avoids equipment damage. The secondary port is normally in a dormant standby state, automatically activating only when the real-time status of the monitoring point connected to the primary port changes. After activation, the secondary port establishes connections with other monitoring points in the same monitoring point group (with the same carbon emission value) and those that have exposed low-level receptor points. Once fully connected, the primary port disconnects from the receptor points at the monitoring points whose real-time status has changed, and the primary port enters a dormant state, thus completing seamless replacement of monitoring points. Therefore, by setting up the primary port, secondary port, and transition line for each site, the problems of equipment wear and system oscillation caused by the switching of monitoring points in the control process are solved. It should also be noted that sensing points can be set at the receptor points of the monitoring points, and secondary sensing points can be set at the corresponding control points. The sensing points and secondary sensing points are virtually connected to form a sensing line. The control points monitor the sensing points, and the secondary sensing points change synchronously when the state of the sensing points changes, achieving real-time sensing of the monitoring points. Specifically, a virtual sensing line is established between the monitoring points and the corresponding control points as a state synchronization channel. The sensing points and secondary sensing points establish a permanent virtual connection through lightweight communication protocols (such as MQTT and WebSocket). The sensing points reflect whether the receptor points are connected to the site, and the secondary sensing points move in real-time accordingly. In detail, sensing... A point is essentially a state synchronization unit set up on a receptor point to reflect whether the receptor point is connected to a site. A secondary sensing point is essentially a synchronization response strategy set up on a control point to link with the sensing point in real time and realize real-time feedback of the monitoring point's state. A sensing line is essentially a virtual communication link established between the sensing point and the secondary sensing point to realize real-time synchronization and accurate sensing of the state between the monitoring point and the control point. When a sensing point changes from idle to connected (e.g., from "idle" to "carried" or "connected"), the secondary sensing point changes synchronously. After the control point detects the state change, it confirms that the monitoring points have grouped together and performs emission reduction operations.

[0033] In one embodiment, the control unit includes: An execution unit is used to perform carbon emission control on the control points corresponding to the site-linked monitoring group, wherein the carbon emission control includes performing control operations on the control points corresponding to the site-linked monitoring group; The disbanding unit is used to determine that carbon emission control has been completed when the difference after control is greater than or equal to the warning threshold, and to disband the site-linked monitoring group.

[0034] It should be noted that the execution unit is used to issue carbon emission control instructions to the corresponding control points after the monitoring points have completed their free grouping. The control points, acting as the grouped monitoring point group, receive the instructions and perform control operations such as shutdown, startup, or parameter adjustment on the equipment bound to the corresponding monitoring points. By adjusting the equipment's operating status, group-based centralized emission reduction is achieved, rapidly reducing the overall carbon emissions of the park. The disbanding unit is used to recalculate the difference between the target total carbon emissions and the total carbon emissions after the carbon emission control operations are executed, through the early warning module. When this difference rises to a level greater than or equal to the early warning threshold, the carbon emission control target for this round is determined to be achieved. The system automatically removes the markings of the sites on the monitoring point group, and the sites are in an unconnectable state. At this time, the sites... The monitoring point automatically disconnects from other monitoring points within the monitoring point cluster and from the receptor points on the monitoring point, thus completing the disbanding process (i.e., terminating the connection between the monitoring point and the receptor point, canceling the carrying (connection) state of the monitoring point to the monitoring point, and disbanding the monitoring point from the monitoring cluster). This restores each monitoring point to its normal state of independent monitoring and operation, waiting for the next clustering trigger condition to be met to re-execute the clustering and control process. Furthermore, through the free clustering and disbanding of monitoring points, a dynamic, intelligent, and refined IoT management system for carbon emissions in the park is constructed. This enables real-time association and collaborative control between macro-level emission targets (total carbon emissions) and micro-level equipment through virtual monitoring points and control points, thereby achieving efficient and accurate carbon emission management. Specifically, the essence of disbanding is: the status of the site is restored from "connected" to "idle" or "to be marked", the status of the receptor point is restored from "carried" to "to be exposed", and each site is unbound (disconnected) from its connected receptor point; its essence is: to clear the temporary binding relationship of "task-executor", so that the site returns to the control center and the monitoring point returns to an independent state, that is, to reclaim the site cluster marked this time and its individual sites, and to clear or reset the integer value of the site, thereby releasing the computing resources and memory occupied by the site.

[0035] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An Internet of Things-based real-time monitoring and early warning system for carbon emissions in a park, characterized in that, include: The configuration module is used to divide the park into grids to obtain a multi-scale spatial grid, identify all devices with carbon emissions within the multi-scale spatial grid, configure a monitoring point for each device, configure a control center for all monitoring points, and the control center is configured with multiple control points. The accounting module is used to calculate the total carbon emissions of the park for each preset time period based on a multi-scale spatial grid. The early warning module is used to determine the difference between the target total carbon emissions and the total carbon emissions, and to determine whether the difference is less than the preset early warning threshold. The control module is used to freely group multiple monitoring points based on preset site clusters when the difference is less than the warning threshold, to obtain site-connected monitoring clusters, and to control carbon emissions based on site-connected monitoring clusters until the difference is greater than or equal to the warning threshold. The visualization module is used to display multi-scale spatial grids and monitoring points.

2. The IoT-based real-time monitoring and early warning system for carbon emissions in industrial parks according to claim 1, characterized in that, The configuration module includes: A dividing unit is used to divide the park into grids to obtain a multi-scale spatial grid, wherein the multi-scale spatial grid includes a first-level grid, a second-level grid, and a third-level grid; The determination unit is used to determine the carbon source classification system of the park, and based on the carbon source classification system, to determine all equipment in the park that emits carbon. A configuration unit is used to configure a monitoring point for each device in the three-level grid on a one-to-one basis, wherein the monitoring point is bound to the device number configured therewith, and a monitoring point number is configured for each monitoring point; The control unit is used to configure a control center for all monitoring points. The control center corresponds to multiple control points. Each control point is connected to a device and the multiple control points are connected to all monitoring points in a one-to-one correspondence. The control center is deployed on a cloud platform.

3. The IoT-based real-time monitoring and early warning system for carbon emissions in industrial parks according to claim 1, characterized in that, The accounting module includes: The calculation unit is used to calculate the real-time carbon emissions of the park for each preset time period using a multi-scale spatial grid, and obtain the total carbon emissions of the park.

4. The IoT-based real-time monitoring and early warning system for carbon emissions in industrial parks according to claim 1, characterized in that, The early warning module includes: The preset unit is used to determine the target total carbon emissions for each preset time period within the park and to preset the early warning threshold. The early warning unit is used to obtain the difference between the target total carbon emissions and the total carbon emissions, and to determine whether the difference is less than the preset early warning threshold.

5. The IoT-based real-time monitoring and early warning system for carbon emissions in industrial parks according to claim 1, characterized in that, The control module includes: The clustering unit is used to set clustering trigger conditions and, based on the clustering trigger conditions, to freely cluster multiple monitoring points according to preset site clusters; The control unit is used to control carbon emissions from monitoring sites based on free association, and to disband the monitoring group linked to the sites after the carbon emission control is completed.

6. A real-time monitoring and early warning system for carbon emissions in a park based on the Internet of Things, as described in claim 5, is characterized in that... The clustering unit includes: The setting unit is used to set multiple receptor points for each monitoring point. The multiple receptor points correspond to the real-time status of the monitoring point. The receptor points are exposed according to the real-time status of the monitoring point. The real-time status and the receptor points include extremely high level, high level, medium level and low level. The multiple real-time statuses correspond one-to-one with the multiple receptor points. Each receptor point is bound to the carbon emission code of the corresponding monitoring point. The carbon emission code of the monitoring point is obtained by mapping the carbon emission of the monitoring point through a mapping table. The allocation unit is used to set up multiple sites corresponding to the control center and allocate the differences to obtain multiple individual differences. Each site is bound to a corresponding individual difference code, and the individual difference code is obtained by mapping the individual differences through a mapping table. The linker unit is used to link multiple sites one-to-one based on multiple monomer differences to form a site cluster, and to use the sites on the site cluster to bind with the exposed receptor sites on the monitoring point to obtain the site-linked monitoring cluster.

7. A real-time monitoring and early warning system for carbon emissions in a park based on the Internet of Things, as described in claim 6, is characterized in that... The step of allocating the differences to obtain multiple individual differences includes: All monitoring points exposed to low-level receptors were screened to form a primary candidate set. The number of monitoring points with the same carbon emissions in the candidate set was counted. Monitoring points with the same carbon emissions were grouped into the same monitoring point group and sorted in descending order of the number of monitoring points in each group. Starting with the group of monitoring points with the largest number, priority is given to selecting monitoring points within the group that expose low-level receptors. Monitoring points within the group are selected sequentially until the sum of the carbon emissions of all selected monitoring points equals the difference. The carbon emissions corresponding to each selected monitoring point are considered as a single-unit difference. This process is repeated to obtain multiple single-unit differences. If the carbon emissions of monitoring points in the primary candidate set are less than the difference, monitoring points exposed to medium-level receptors are used for supplementary screening. This process is repeated until the sum of the carbon emissions of all selected monitoring points equals the difference.

8. A real-time monitoring and early warning system for carbon emissions in a park based on the Internet of Things, as described in claim 5, is characterized in that... The step of connecting multiple sites based on one-to-one labeling of multiple monomer differences to form a site cluster, and then using the sites on the site cluster to bind with the exposed receptor sites on the monitoring points to obtain the site-linked monitoring cluster includes: Multiple sites within the control center with the same numerical value as the monomer difference are labeled one-to-one based on multiple monomer differences, and the labeled sites are connected to obtain site clusters; Multiple sites on the site cluster are connected to the carbon emission codes of the exposed receptor sites on multiple monitoring points through their own bound monomer difference codes. After connection, the multiple sites on the site cluster carry the carbon emission codes of the receptor sites they are connected to, thus obtaining the site-linked monitoring cluster.

9. A real-time monitoring and early warning system for carbon emissions in a park based on the Internet of Things, as described in claim 1, is characterized in that... The control unit includes: An execution unit is used to perform carbon emission control on the control points corresponding to the site-linked monitoring group, wherein the carbon emission control includes performing control operations on the control points corresponding to the site-linked monitoring group; The disbanding unit is used to determine that carbon emission control has been completed when the difference after control is greater than or equal to the warning threshold, and to disband the site-linked monitoring group.

Images