Distributed rail transit carbon emission monitoring system

Abstract

The present invention relates to the field of carbon dioxide monitoring technology, and in particular to a distributed rail transit carbon emission monitoring system. The energy consumption data, carbon emission data and operation data of each terminal device are acquired through a terminal data acquisition module and a distributed data acquisition module, and a comprehensive analysis is performed through a carbon emission integration module. The prediction acquisition module also preliminarily determines whether the carbon emission data is normal based on the consistency of the carbon emission high-point track segment and the floating carbon emission high-point track segment, and matches the data with the operation data to determine the corresponding carbon emission optimization method, which is helpful to predict future carbon emission trends and take corresponding optimization measures, thereby reducing carbon emissions. The system provided by the present invention can accurately monitor and evaluate carbon emission data, and reduce carbon emissions by predicting and optimizing carbon emission methods, thereby helping to achieve the purpose of environmental protection, emission reduction and resource utilization optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon dioxide monitoring, and in particular to a distributed rail transit carbon emission monitoring system. Background Art

[0002] The carbon emission monitoring system involves sensor technology (such as gas sensors, optical sensors), data collection and transmission technology (including wireless communication and Internet of Things technology), data processing and analysis technology (such as big data processing, data mining and artificial intelligence), cloud computing technology, monitoring system design, reporting and early warning technology, and visual interface technology. These technologies together constitute a complete monitoring system that can realize real-time monitoring, data analysis and report generation of carbon emissions, providing important support and decision-making reference for environmental protection and carbon emission reduction.

[0003] Chinese patent publication number CN117630284A discloses a distributed carbon emission monitoring system and method, including: a distributed data acquisition terminal, a data analysis and processing module and a data display module; the distributed data acquisition terminal is used to collect environmental data and transmit the collected environmental data; the data analysis and processing module is used to calculate the carbon dioxide emissions based on the measured carbon emission formula of temperature and pressure compensation for environmental data, and compare the carbon dioxide emissions with the preset carbon dioxide emissions threshold, and output alarm information according to the comparison result; the data display module is used to display the current carbon dioxide emissions, historical carbon dioxide emissions and the corresponding data change line, and issue an alarm message on the display platform according to the comparison result to remind users to pay attention to carbon emissions. The invention realizes carbon dioxide emission monitoring in areas with fixed emission sources, and has the technical advantages of real-time and reliable. It can be seen that the invention has the following problems: it only monitors the carbon dioxide emissions in each area, but does not determine the law of carbon dioxide emissions in each area, nor optimizes the carbon dioxide emissions according to the law of carbon dioxide emissions. Summary of the invention

[0004] To this end, the present invention provides a distributed rail transit carbon emission monitoring system to overcome the problem in the prior art that rail transit transportation operation cannot be adjusted in time according to operation data, resulting in high rail transit carbon emissions.

[0005] To achieve the above objectives, the present invention provides a distributed rail transit carbon emission monitoring system, comprising:

[0006] A terminal data acquisition module is provided on each rail transit terminal device to acquire energy consumption data and carbon emission data of each terminal device;

[0007] A distributed data acquisition module is used to obtain the operating data of each terminal device;

[0008] a carbon emission integration module, which is connected to the terminal data acquisition module and the distribution data acquisition module respectively, and is used to determine the carbon emission equivalent of a single terminal device in each track segment according to the energy consumption data, the carbon emission data and the operation data, and to determine the carbon emission high-point track segment of a single terminal device and the carbon emission high-point terminal device of a single track segment in combination with the carbon emission equivalent of each terminal device in a single track segment, so as to determine the floating carbon emission high-point track segment;

[0009] A prediction acquisition module, which is respectively connected to the terminal data acquisition module, the distribution data acquisition module and the carbon emission integration module, and is used to preliminarily determine whether the carbon emission data is normal according to the consistency of the carbon emission high point track segment and the floating carbon emission high point track segment, and match it with the operation data to determine the corresponding carbon emission optimization method;

[0010] The operation data includes the passing station information, time information, track length information between stations, and station traffic information.

[0011] Furthermore, the energy consumption data is indirectly generated carbon emission data, including direct electricity consumption data and indirect electricity consumption data of each terminal device;

[0012] The direct electricity consumption data includes electricity consumption data generated by a power grid connected to each terminal device, and the indirect electricity consumption data includes electricity consumption data generated by a power battery in each terminal device.

[0013] Furthermore, the carbon emission data is directly generated carbon emission data, including the carbon dioxide content detected in each terminal device and the carbon dioxide content emitted by each terminal device.

[0014] Furthermore, the carbon emission integration module determines the number of track segments of a single terminal device based on the operating data, and determines the carbon emission equivalent of the single terminal device in each track segment based on the energy consumption data and the carbon emission data.

[0015] Furthermore, the carbon emission integration module determines the carbon emission high-point track segment of a single terminal device according to the carbon emission equivalent of the single terminal device in each track segment, and determines the carbon emission high-point terminal device of a single track segment according to the carbon emission equivalent of each terminal device in a single track segment.

[0016] Furthermore, the carbon emission integration module determines the proportion of the carbon emission high point trajectory segments corresponding to all operations of the terminal devices having the same operating data as the corresponding terminal devices according to the carbon emission high point trajectory segments of the single terminal devices to determine the floating carbon emission high point trajectory segments.

[0017] Further, the prediction acquisition module preliminarily determines whether the carbon emission equivalent is normal according to the consistency between the carbon emission high point track segment and the floating carbon emission high point track segment of the single terminal device;

[0018] If the carbon emission high point trajectory segment and the floating carbon emission high point trajectory segment are consistent, the prediction acquisition module preliminarily determines that the carbon emission equivalent is normal;

[0019] If the carbon emission high point trajectory segment and the floating carbon emission high point trajectory segment are inconsistent, the prediction acquisition module preliminarily determines that the carbon emission equivalent is abnormal.

[0020] Further, under the condition that the carbon emission equivalent is initially determined to be normal, the prediction acquisition module determines the carbon emission terminal optimization mode of the corresponding rail transit terminal equipment according to whether the length information and flow information of the carbon emission high point track segment and the corresponding track segment match, wherein:

[0021] If the carbon emission high point track segment matches the length information and flow information of the corresponding track segment respectively, the prediction acquisition module determines that the carbon emission of the corresponding terminal device is normal, and determines that the optimization method is to add a passing station to the current carbon emission high point track segment;

[0022] If there is length information between the carbon emission high-point track segment and the corresponding track segment, and / or the flow information between the carbon emission high-point track segment and the corresponding track segment does not match, the prediction acquisition module determines that the carbon emissions of the corresponding terminal equipment are abnormal, and determines that the optimization method is to repair the corresponding abnormal track segment.

[0023] Further, under the condition of preliminary determination of abnormal carbon emission equivalent, the prediction acquisition module determines the optimization method according to the fluctuation amount of the carbon emission curve of each terminal device in each track section in a single operation;

[0024] If the fluctuation exceeds the set value, the prediction acquisition module determines that there is an abnormal track segment, and determines the optimization method to repair the corresponding abnormal track segment;

[0025] If the fluctuation does not exceed the set value, and the average value of the fluctuation is greater than the average value of the same period in history, the prediction acquisition module determines that there is an abnormality in the corresponding terminal device, and determines that the optimization method is to repair the corresponding terminal device.

[0026] Furthermore, when the prediction and acquisition module determines that the carbon emissions of the terminal device are normal, the prediction and acquisition module determines the location of the added transit station based on the carbon emission ratio between the current carbon emission high point track segment and the corresponding adjacent track segment.

[0027] Compared with the prior art, the beneficial effect of the present invention lies in that the distributed rail transit carbon emission monitoring system provided by the present invention can obtain the energy consumption data, carbon emission data and operation data of each terminal device through the terminal data acquisition module and the distributed data acquisition module, and conduct a comprehensive analysis through the carbon emission integration module, so as to accurately determine the carbon emission equivalent of a single terminal device in each track segment, as well as the floating carbon emission high-point track segment, which is helpful to accurately monitor and evaluate the carbon emission situation; and, by combining the carbon emission equivalent of each terminal device in a single track segment, determining the carbon emission high-point track segment of a single terminal device and the carbon emission high-point terminal device of a single track segment, it is helpful to determine the key areas and equipment of carbon emissions, and provide a basis for targeted carbon emission management.

[0028] Furthermore, the system provided by the present invention preliminarily determines whether the carbon emission data is normal based on the consistency of the carbon emission high-point track segment and the floating carbon emission high-point track segment through the prediction acquisition module, and matches it with the operation data to determine the corresponding carbon emission optimization method, which helps to predict future carbon emission trends and take corresponding optimization measures to reduce carbon emissions; the distributed rail transit carbon emission monitoring system provided by the present invention can realize accurate monitoring and evaluation of carbon emission data, determine key areas and equipment, and reduce carbon emissions by predicting and optimizing carbon emission methods, thereby helping to achieve the purpose of environmental protection emission reduction and resource utilization optimization.

[0029] Furthermore, the system of the present invention that monitors and manages energy consumption data and carbon emission data generated directly and indirectly can help achieve more refined carbon emission management, improve energy utilization efficiency, and promote the development of carbon emission reduction work, thereby providing strong support for the sustainable development of the rail transit industry.

[0030] Furthermore, the carbon emission integration module in the present invention helps to accurately locate carbon emission high points, identify floating carbon emission high point track sections, and achieve refined carbon emission management, providing important technical support and decision-making basis for carbon emission reduction work in rail transit systems.

[0031] Furthermore, the prediction and acquisition module in the present invention can accurately determine carbon emissions, optimize carbon emission management strategies, and quickly respond to abnormal situations to improve operational efficiency, providing important support and guidance for carbon emission management and operational optimization of rail transit systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a connection diagram of a distributed rail transit carbon emission monitoring system according to an embodiment of the present invention;

[0033] Figure 2 This is a workflow diagram of a distributed rail transit carbon emission monitoring system according to an embodiment of the present invention;

[0034] Figure 3 A diagram showing the relationship between track segments and passing stations of a distributed rail transit carbon emission monitoring system according to an embodiment of the present invention;

[0035] Figure 4 A schematic diagram of the locations of the passing stations is added to the embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0037] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0038] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0039] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0040] See also Figure 1 and Figure 2 As shown, it is a connection diagram of a distributed rail transit carbon emission monitoring system according to an embodiment of the present invention and a work flow diagram of a distributed rail transit carbon emission monitoring system according to an embodiment of the present invention. The present invention provides a distributed rail transit carbon emission monitoring system, comprising:

[0041] A terminal data acquisition module is provided on each rail transit terminal device to acquire energy consumption data and carbon emission data of each terminal device;

[0042] A distributed data acquisition module is provided on each terminal device to acquire the operation data of each terminal device;

[0043] a carbon emission integration module, which is connected to the terminal data acquisition module and the distribution data acquisition module respectively, and is used to determine the carbon emission equivalent of a single terminal device in each track segment according to the energy consumption data, the carbon emission data and the operation data, and to determine the carbon emission high-point track segment of a single terminal device and the carbon emission high-point terminal device of a single track segment in combination with the carbon emission equivalent of each terminal device in a single track segment, so as to determine the floating carbon emission high-point track segment;

[0044] A prediction acquisition module, which is respectively connected to the terminal data acquisition module, the distribution data acquisition module and the carbon emission integration module, and is used to preliminarily determine whether the carbon emission data is normal according to the consistency of the carbon emission high point track segment and the floating carbon emission high point track segment, and match it with the operation data to determine the corresponding carbon emission optimization method;

[0045] The operation data includes the passing station information, time information, track length information between stations, and station traffic information.

[0046] It is understandable that the time information includes the departure time at the originating station, the arrival time and departure time at each transit station, and the arrival time at the terminal station.

[0047] Specifically, energy consumption data refers to indirectly generated carbon emission data, including direct electricity consumption data and indirect electricity consumption data of each terminal device;

[0048] The direct electricity consumption data includes electricity consumption data generated by directly using a power grid connected to each terminal device, and the indirect electricity consumption data includes electricity consumption data generated by using a power battery in each terminal device.

[0049] It is understandable that if the indirect electricity consumption uses electricity generated by renewable energy, it does not belong to the indirect electricity consumption data. For example, if the power battery uses photovoltaic power generation or wind power generation when charging, it does not belong to the indirect electricity consumption data.

[0050] The calculation method for converting electricity consumption into carbon emissions includes: (1) calculating the carbon emission factor to determine the carbon emission factor of the region where the terminal equipment is located or the source of electricity used. The carbon emission factor represents the carbon dioxide emissions corresponding to each kilowatt-hour of electricity consumed in grams per kilowatt-hour (gCO2 / kWh); (2) calculating the carbon emissions of direct electricity consumption. The carbon emissions of direct electricity consumption are equal to the amount of electricity directly consumed × the carbon emission factor; (3) calculating the carbon emissions of indirect electricity consumption. The carbon emissions of indirect electricity consumption are equal to the indirect electricity consumption × the carbon emission factor; (4) total carbon emissions. The total carbon emissions are obtained by adding the carbon emissions of direct electricity consumption and indirect electricity consumption.

[0051] For example, during the operation of a terminal device, the direct electricity consumption is 100kWh, the indirect electricity consumption is 50kWh, and the electricity carbon emission factor in the area is 0.5gCO2 / kWh; then the carbon emissions from direct electricity consumption are 100kWh×0.5gCO2 / kWh=50gCO2, and the carbon emissions from indirect electricity consumption are 50kWh×0.5gCO2 / kWh=25gCO2. Therefore, the indirect carbon emission equivalent is 50gCO2+25gCO2=75gCO2, that is, the total carbon dioxide emissions of the terminal device are 75 grams of CO2.

[0052] In implementation, the carbon emission integration module includes a networking unit, which pre-stores energy statistical reports of various regions (including carbon emission factors); it also includes a positioning unit to locate the location of the terminal equipment in real time; when the location of the terminal equipment changes, the carbon emission integration module obtains the corresponding carbon emission factor from the networking unit to convert the energy consumption data into carbon emission equivalents.

[0053] Specifically, the carbon emission data is directly generated carbon emission data, including the carbon dioxide content detected in each terminal device and the carbon dioxide content emitted by each terminal device.

[0054] It can be understood that the carbon dioxide content detected in each terminal device is the carbon dioxide produced by the breathing of passengers riding in the terminal device; the carbon dioxide content emitted by each terminal device is the carbon dioxide content emitted when each terminal device uses fossil fuels such as oil or natural gas to drive the terminal device to move according to the operating route.

[0055] In implementation, a carbon dioxide sensor can be installed inside each terminal device to monitor the carbon dioxide concentration in the air inside the terminal device to determine the amount of carbon dioxide emitted; an exhaust emission detector can be installed at the exhaust gas of each terminal device to monitor and analyze the fuel used to determine the carbon dioxide content emitted by the terminal device to determine the amount of carbon dioxide emitted; at this time, direct carbon emission equivalent = the amount of carbon dioxide inside the terminal device + the amount of carbon dioxide emitted by the terminal device.

[0056] Specifically, the carbon emission integration module determines the number of track segments of a single terminal device based on the operating data, and determines the carbon emission equivalent of the single terminal device in each track segment based on the energy consumption data and the carbon emission data.

[0057] See also Figure 3As shown, it is a relationship diagram between track segments and passing stations of the distributed rail transit carbon emission monitoring system of an embodiment of the present invention. The carbon emission integration module determines the number of track segments of a single terminal device based on the passing station information in the operation data, that is, the number of track segments of a single terminal device = the number of passing stations + 1. In each track segment, the carbon emission integration module determines the carbon emission equivalent of the terminal device based on the energy consumption data and carbon emission data. The carbon emission equivalent of a single track segment = the direct carbon emission equivalent of the track segment + the indirect carbon emission equivalent of the track segment.

[0058] Specifically, the carbon emission integration module determines the carbon emission high-point track segments of individual terminal devices according to the carbon emission equivalents of the individual terminal devices in each track segment, and determines the carbon emission high-point terminal devices of a single track segment according to the carbon emission equivalents of each terminal device in a single track segment.

[0059] It can be understood that the track segment with the largest carbon emission equivalent in each track segment during a single operation of a single terminal device is recorded as the carbon emission high-point track segment of the single terminal device; for each terminal device with the same operating data, the terminal device with the largest carbon emission equivalent in each track segment is recorded as the carbon emission high-point terminal device of the single track segment.

[0060] By determining the carbon emission equivalent of a single terminal device in each track section, this system can accurately identify the carbon emissions of each terminal device in different track sections, thereby accurately locating carbon emission peaks, which helps managers take targeted emission reduction measures for specific track sections or specific terminal devices to achieve the goal of reducing carbon emissions.

[0061] Specifically, the carbon emission integration module determines the proportion of carbon emission high point trajectory segments corresponding to all operations of terminal devices with exactly the same operation data as the corresponding terminal device based on the carbon emission high point trajectory segment of the single terminal device to determine the floating carbon emission high point trajectory segment.

[0062] In one embodiment, there are three terminal devices A, B and C, and the operating data of A, B and C are exactly the same and A runs twice, B runs three times and C runs once, then the carbon emission high-point track segments corresponding to the three terminal devices running a total of 6 times are counted, and the track segment with the largest proportion of carbon emission high-point track segments is recorded as the floating carbon emission high-point track segment; for example, the carbon emission high-point track segments of A's two runs and B's two runs are both the second segment, the carbon emission high-point track segment of B's ​​one run and the carbon emission high-point track segment of C's one run are both the third segment, then the second segment accounts for two-thirds, the third segment accounts for one-third, and the floating track segment is the second segment.

[0063] This system determines the proportion of high-carbon emission track sections corresponding to the entire operation of terminal equipment with exactly the same operating data as the corresponding terminal equipment based on the high-carbon emission track sections of a single terminal equipment, thereby identifying floating carbon emission high-point track sections, which helps to find track sections with higher carbon emissions under specific conditions and provide guidance for optimizing train scheduling, energy allocation and emission reduction strategies.

[0064] Specifically, the prediction acquisition module preliminarily determines whether the carbon emission equivalent is normal according to the consistency of the carbon emission high point track segment and the floating carbon emission high point track segment of the single terminal device;

[0065] If the carbon emission high point trajectory segment and the floating carbon emission high point trajectory segment are consistent, the prediction acquisition module preliminarily determines that the carbon emission equivalent is normal;

[0066] If the carbon emission high point trajectory segment and the floating carbon emission high point trajectory segment are inconsistent, the prediction acquisition module preliminarily determines that the carbon emission equivalent is abnormal.

[0067] When the carbon emission high point orbit segment and the floating carbon emission high point orbit segment of a single terminal device are the same, it is recorded as the carbon emission high point orbit segment and the floating carbon emission high point orbit segment are consistent.

[0068] It can be understood that the floating carbon emission high point track segment is determined by all operation records of all terminal devices with the same operation data before the current date, and the floating carbon emission high point track segment is updated after the last terminal device with the same operation data is completed. For example, the terminal devices A, B, and C corresponding to a certain operation data run 6 times a day for a total of one week. The floating carbon emission high point track segment on the eighth day is updated after the sixth operation on the seventh day. The floating carbon emission high point track segment corresponding to the eighth day is selected based on 6×7=42 groups of operation data.

[0069] By conducting a comprehensive analysis of the carbon emissions of individual terminal devices, this system helps managers achieve refined carbon emissions management. Based on the carbon emission equivalents of individual terminal devices in each track section and the determination of track sections with high carbon emissions, targeted carbon emissions monitoring, evaluation and control can be carried out, thereby improving the efficiency and accuracy of carbon emissions management.

[0070] Specifically, when the carbon emission equivalent is initially determined to be normal, the prediction acquisition module determines the carbon emission terminal optimization mode of the corresponding rail transit terminal equipment according to whether the length information and flow information of the carbon emission high point track segment match the corresponding track segment, wherein:

[0071] If the carbon emission high point track segment matches the length information and flow information of the corresponding track segment respectively, the prediction acquisition module determines that the carbon emission of the corresponding terminal device is normal, and the optimization method determined by the prediction acquisition module is to add a passing station to the current carbon emission high point track segment;

[0072] If there is length information between a track segment with high carbon emissions and a corresponding track segment, and / or the flow information between the track segment with high carbon emissions and the corresponding track segment does not match, the prediction and acquisition module determines that the carbon emissions of the corresponding terminal device are abnormal, and the optimization method determined by the prediction and acquisition module is to repair the corresponding abnormal track segment.

[0073] It can be understood that the carbon emission equivalent of each track segment is positively correlated with the length information of the corresponding track segment, and the carbon emission equivalent of each track segment is also positively correlated with the flow information of the corresponding track segment; then, a graph with the carbon emission equivalent of each track segment as the vertical axis and the length information of the corresponding track segment as the horizontal axis should be a positively correlated function; similarly, a graph with the carbon emission equivalent of each track segment as the vertical axis and the flow information of the corresponding track segment as the horizontal axis should also be a positively correlated function.

[0074] Therefore, if both images are positively correlated functions, it is determined that the carbon emission high-point track segment matches the length information and flow information of the corresponding track segment respectively; if any one of the images is not a positively correlated function, it is determined that there is a carbon emission high-point track segment and the length information of the corresponding track segment, and / or the flow information of the carbon emission high-point track segment does not match the corresponding track segment, and the carbon emission of the corresponding terminal device is determined to be abnormal.

[0075] When determining that the carbon emissions of the terminal equipment are abnormal, the abnormal track segment is determined based on the points in the image that are not positively correlated, and the track segment is inspected and repaired to solve the problem of abnormal carbon emissions.

[0076] The prediction acquisition module can help the system accurately determine whether the carbon emission equivalent of a single terminal device is normal by preliminarily determining the consistency of the carbon emission high point track segment and the floating carbon emission high point track segment. This helps to detect abnormal carbon emissions early and improve managers' monitoring and control capabilities of carbon emissions.

[0077] Specifically, under the condition of preliminary determination of abnormal carbon emission equivalent, the prediction acquisition module determines the optimization method according to the fluctuation amount of the carbon emission curve of each terminal device in each track section in a single operation;

[0078] If the fluctuation exceeds the set value, the prediction acquisition module determines that there is an abnormal track segment, and the optimization method determined by the prediction acquisition module is to repair the corresponding abnormal track segment;

[0079] If the fluctuation does not exceed the set value, and the average value of the fluctuation is greater than the average value of the same period in history, the prediction acquisition module determines that there is an abnormality in the corresponding terminal device, and the optimization method determined by the prediction acquisition module is to repair the corresponding terminal device.

[0080] It can be understood that a carbon emission curve is drawn with each track segment of a single run as the horizontal axis and the corresponding carbon emission equivalent as the vertical axis, wherein the fluctuation of the carbon emission curve = the highest carbon emission equivalent - the lowest carbon emission equivalent.

[0081] In implementation, the set value is the sum of the standard deviation of carbon emission equivalent and the tolerance error, where the tolerance error>0, preferably, the tolerance error=one tenth of the minimum carbon emission equivalent; that is, the set value=the standard deviation of carbon emission equivalent+one tenth of the minimum carbon emission equivalent. In one embodiment, there are three track segments, and the corresponding carbon emission equivalents are e, f, and g, then the standard deviation of carbon emission equivalent 2=[(ex)2+(fx)2+(gx)2]÷3, where x=(e+f+g) / 3.

[0082] It can be understood that the flow rate corresponding to a single track section = the flow rate of the previous track section + the flow rate of passengers boarding at the previous station - the flow rate of passengers getting off at the previous station.

[0083] When the prediction acquisition module determines that carbon emissions are abnormal, it can determine the abnormal track section based on the fluctuation of the carbon emission curve and propose corresponding optimization methods. This helps the system to quickly respond to abnormal carbon emissions, take timely measures to repair and improve, and ensure the stable operation of the rail transit system.

[0084] Specifically, when the prediction and acquisition module determines that the carbon emissions of the terminal equipment are normal, the prediction and acquisition module determines the location of the added transit station based on the carbon emission ratio of the current carbon emission high-point track segment and the corresponding adjacent track segment (the previous track segment and the next track segment adjacent to the track segment).

[0085] See also Figure 4 As shown, it is a schematic diagram of the location of the passing station added in an embodiment of the present invention. The carbon emission ratio of the current carbon emission high point track segment and the corresponding previous track segment and the next track segment = (carbon emission equivalent of the carbon emission high point track segment + carbon emission equivalent of the previous track segment): (carbon emission equivalent of the carbon emission high point track segment + carbon emission equivalent of the next track segment), and the location of the passing station is determined according to this ratio. In one embodiment, the ratio is 3:4, then the passing station needs to be built at three sevenths of the carbon emission high point track segment from the running direction.

[0086] The prediction acquisition module determines the optimization method of carbon emission terminals according to different situations, including adding passing stations or repairing abnormal track sections. By optimizing the carbon emission management strategy of the rail transit system, carbon emissions can be effectively reduced, and operational efficiency and environmental protection levels can be improved; adding passing stations in the prediction acquisition module can help improve the operational efficiency of the rail transit system, optimize carbon emission management strategies and operating methods, help reduce energy consumption costs, reduce environmental pollution, and thus achieve the goal of sustainable development.

[0087] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0088] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A distributed rail transit carbon emission monitoring system, characterized in that: include: A terminal data acquisition module is provided on each rail transit terminal device to acquire energy consumption data and carbon emission data of each terminal device; A distributed data acquisition module is used to acquire the operating data of each terminal device; a carbon emission integration module, which is connected to the terminal data acquisition module and the distribution data acquisition module respectively, and is used to determine the carbon emission equivalent of a single terminal device in each track segment according to the energy consumption data, the carbon emission data and the operation data, and to determine the carbon emission high-point track segment of a single terminal device and the carbon emission high-point terminal device of a single track segment in combination with the carbon emission equivalent of each terminal device in a single track segment, so as to determine the floating carbon emission high-point track segment; The carbon emission integration module determines the number of track segments of a single terminal device according to the operation data, and determines the carbon emission equivalent of the single terminal device in each track segment according to the energy consumption data and the carbon emission data; The carbon emission integration module determines the proportion of the carbon emission high point trajectory segments corresponding to all operations of the terminal equipment having the same operation data as the corresponding terminal equipment according to the carbon emission high point trajectory segment of the single terminal equipment to determine the floating carbon emission high point trajectory segment; A prediction acquisition module, which is respectively connected to the terminal data acquisition module, the distribution data acquisition module and the carbon emission integration module, and is used to preliminarily determine whether the carbon emission data is normal according to the consistency of the carbon emission high point track segment and the floating carbon emission high point track segment, and match it with the operation data to determine the corresponding carbon emission optimization method; The prediction acquisition module preliminarily determines whether the carbon emission equivalent is normal according to the consistency between the carbon emission high point track segment and the floating carbon emission high point track segment of the single terminal device; If the carbon emission high point trajectory segment and the floating carbon emission high point trajectory segment are consistent, the prediction acquisition module preliminarily determines that the carbon emission equivalent is normal; If the carbon emission high point trajectory segment and the floating carbon emission high point trajectory segment are inconsistent, the prediction acquisition module preliminarily determines that the carbon emission equivalent is abnormal; Under the condition that the carbon emission equivalent is initially determined to be normal, the prediction acquisition module determines the carbon emission terminal optimization mode of the corresponding rail transit terminal equipment according to whether the length information and flow information of the carbon emission high point track segment match the corresponding track segment, wherein: If the carbon emission high point track segment matches the length information and flow information of the corresponding track segment respectively, the prediction acquisition module determines that the carbon emission of the corresponding terminal device is normal, and determines that the optimization method is to add a passing station to the current carbon emission high point track segment; If there is length information of the carbon emission high point track segment and the corresponding track segment, and / or the flow information of the carbon emission high point track segment and the corresponding track segment does not match, the prediction acquisition module determines that the carbon emission of the corresponding terminal device is abnormal, and determines that the optimization method is to repair the corresponding abnormal track segment; The operation data includes the passing station information, time information, track length information between stations, and station traffic information.

2. The distributed rail transit carbon emission monitoring system according to claim 1 is characterized in that: The energy consumption data is indirectly generated carbon emission data, including direct electricity consumption data and indirect electricity consumption data of each terminal device; The direct electricity consumption data includes electricity consumption data generated by a power grid connected to each terminal device, and the indirect electricity consumption data includes electricity consumption data generated by a power battery in each terminal device.

3. The distributed rail transit carbon emission monitoring system according to claim 1 is characterized in that: The carbon emission data is directly generated carbon emission data, including the carbon dioxide content detected in each terminal device and the carbon dioxide content emitted by each terminal device.

4. The distributed rail transit carbon emission monitoring system according to claim 1 is characterized in that: The carbon emission integration module determines the carbon emission high-point track segment of a single terminal device according to the carbon emission equivalent of the single terminal device in each track segment, and determines the carbon emission high-point terminal device of a single track segment according to the carbon emission equivalent of each terminal device in a single track segment.

5. The distributed rail transit carbon emission monitoring system according to claim 1 is characterized in that: Under the condition of preliminary determination of abnormal carbon emission equivalent, the prediction acquisition module determines the optimization method according to the fluctuation amount of the carbon emission curve of each terminal device in each track section in a single operation; If the fluctuation exceeds the set value, the prediction acquisition module determines that there is an abnormal track section, and determines the optimization method to repair the corresponding abnormal track section; If the fluctuation does not exceed the set value, and the average value of the fluctuation is greater than the average value of the same period in history, the prediction acquisition module determines that there is an abnormality in the corresponding terminal device, and determines that the optimization method is to repair the corresponding terminal device.

6. The distributed rail transit carbon emission monitoring system according to claim 1 is characterized in that: When the prediction acquisition module determines that the carbon emissions of the terminal device are normal, the prediction acquisition module determines the location of the added transit station according to the carbon emission ratio of the current carbon emission high point track segment and the corresponding adjacent track segment.

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