Carbon reduction method for urban rail vehicle depot based on entropy weight method-topsis

Abstract

The application discloses a kind of city rail vehicle base carbon reduction methods based on entropy weight method-TOPSIS, with typical city rail vehicle base as object, first system identification covers the 23 whole-link carbon emission points of five big function subareas of vehicle base, constructs the carbon emission accounting system of vehicle base covering direct emission and indirect emission, completes the carbon emission intensity estimation of each point;On this basis, from the emission scale, carbon reduction potential, economy and implementation feasibility multidimension, construct the carbon reduction priority evaluation model based on entropy weight-TOPSIS method, realize the objective quantization ordering of each point carbon reduction value.Result shows, vehicle operation and maintenance operation area is the core contribution area of vehicle base carbon emission, walking part maintenance equipment etc.Point has the highest carbon reduction priority.The application achievement can provide scientific decision basis for the precise carbon reduction work of city rail vehicle base, help the transformation and development of rail transit industry in the direction of green, low carbon.

Description

Technical Field

[0001] This invention relates to the field of urban rail transit technology, specifically to a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS. Background Technology

[0002] With the continuous advancement of urbanization in my country, urban rail transit, with its advantages of large capacity, high efficiency, and low pollution, has become a key infrastructure for alleviating urban traffic congestion and supporting urban development. As a key area for carbon emissions, the low-carbon transformation of the transportation industry has become one of the core tasks in implementing national strategies.

[0003] While urban rail transit is primarily electric-powered, offering significant low-carbon advantages compared to traditional road transportation, its overall energy consumption and carbon emissions continue to increase year by year due to the rapid expansion of the industry. Vehicle depots, as key locations within the urban rail system responsible for vehicle parking, operation, maintenance, and support, are among the areas with the highest concentration of energy consumption and carbon emissions. According to relevant statistics, vehicle depots account for over 30% of the total energy consumption of the urban rail system's operation; therefore, tapping into their carbon reduction potential is crucial for the entire industry to achieve its dual-carbon goals.

[0004] However, current research on carbon emissions from urban rail vehicle depots still has many shortcomings: on the one hand, existing studies mostly focus on macro-level carbon emission accounting of the overall system, lacking detailed carbon emission identification of all aspects and locations within the vehicle depot, making it difficult to accurately locate core emission sources; on the other hand, in the formulation of carbon reduction strategies, most studies only focus on the emission reduction effect of a single technology, lacking a comprehensive priority assessment of carbon reduction at different locations, making it difficult to achieve optimal allocation of carbon reduction resources and failing to support precise and efficient carbon reduction work.

[0005] Against this backdrop, this invention takes a typical urban rail vehicle depot as the research object, conducts carbon emission point identification and accounting throughout the entire process, and constructs a multi-dimensional carbon reduction priority evaluation model. The aim is to clarify the carbon emission structure of the vehicle depot, identify high-value carbon reduction targets, provide scientific theoretical support and practical guidance for the systematic and precise carbon reduction work of the vehicle depot, and help the green and low-carbon transformation of the urban rail transit industry. Summary of the Invention

[0006] This invention provides a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS, which solves the above-mentioned technical problems in the prior art, provides a scientific decision-making basis for the precise carbon reduction work of urban rail vehicle depots, and helps the rail transit industry transform and develop towards a green and low-carbon direction.

[0007] According to the first aspect, one embodiment provides a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS, the method comprising:

[0008] Based on the functional zoning of the urban rail vehicle depot, carbon emission points are identified for each functional zone.

[0009] Taking into account multiple dimensions including emission scale, carbon reduction potential, economic cost, return on investment, and implementation difficulty, a multi-dimensional evaluation index system for carbon emission point carbon reduction priority is constructed.

[0010] Based on the various evaluation indicators of each carbon emission point, the entropy weight method is used to calculate the weight of each evaluation indicator, and the TOPSIS method is combined to rank the carbon reduction priorities of each carbon emission point.

[0011] Furthermore, based on the functional zoning of the urban rail vehicle depot, carbon emission points are identified for each functional zone, specifically including:

[0012] The functional zones of an urban rail vehicle depot include a vehicle operation and maintenance area, a power room, an office and living area, an outdoor work area, and auxiliary facilities.

[0013] Carbon emission points in the vehicle operation and maintenance work area include emission points from train operation / maintenance equipment, emission points from running gear maintenance equipment, emission points from onboard component maintenance, emission points from underboard component maintenance, emission points from car body painting and drying, emission points from car body cleaning, emission points from lifting and transportation equipment, and emission points from warehouse ventilation and dust removal, lighting, and sockets.

[0014] Carbon emission points in the power room include transformer loss emission points, chiller unit emission points, heat pump unit emission points, fire pump unit emission points, air compressor emission points, and reactive power compensation device emission points.

[0015] Carbon emission points in the office and living area include emission points from office equipment, air conditioning in the living area, lighting in the living area, gas emission points in the canteen, and domestic hot water emission points.

[0016] Carbon emission points in outdoor work areas include outdoor lighting emission points and outdoor work equipment emission points;

[0017] Carbon emission points for ancillary facilities include wastewater treatment discharge points and security and communication emission points.

[0018] Furthermore, based on the functional zoning of the urban rail vehicle depot, carbon emission points are identified for each functional zone, specifically including:

[0019] The emission sources of all carbon emission points are divided into two categories: direct emissions and indirect emissions. The annual carbon emissions and carbon emission intensity of carbon emission points are calculated according to the emission source classification.

[0020] Furthermore, taking into account multiple dimensions including emission scale, carbon reduction potential, economic cost, return on investment, and implementation difficulty, a multi-dimensional evaluation index system for prioritizing carbon reduction at carbon emission points is constructed, specifically including:

[0021] The carbon emission point carbon reduction priority evaluation index system includes annual carbon emissions, carbon reduction potential through technology, unit carbon reduction investment cost, investment payback period, and implementation difficulty.

[0022] Furthermore, the entropy weight method is used to calculate the weights of each evaluation index, specifically including:

[0023] a. Construct the initial decision matrix:

[0024]

[0025] Where: n is the number of carbon emission point samples; m is the number of evaluation indicators; For the first The first carbon emission point The original values ​​of each evaluation indicator;

[0026] b. Standardization of indicators, resulting in a standardized matrix. All indicator values ​​are mapped to interval;

[0027] c. Calculating index weights using the entropy weight method:

[0028] The objective weights of each indicator are calculated using information entropy theory. The specific calculation process is as follows:

[0029] Calculate the first Under the evaluation indicators, the first The proportion of indicators for each carbon emission point :

[0030]

[0031] Calculate the first Information entropy of the indicator :

[0032]

[0033] in For standardized coefficients, ensure ;like Then define ;

[0034] Calculate the first Coefficient of difference of the items :

[0035]

[0036] Calculate indicator weights :

[0037] .

[0038] Furthermore, the standardization of indicators specifically includes:

[0039] The indicators are divided into positive and negative indicators, and different standardization formulas are used for each:

[0040] Standardization of positive indicators:

[0041]

[0042] Standardization of negative indicators:

[0043] .

[0044] Furthermore, the TOPSIS method is used to prioritize carbon reduction efforts at each emission point, specifically including:

[0045] a. Constructing a weighted standardized matrix:

[0046] Multiplying the standardized matrix by the indicator weights yields the weighted standardized matrix. :

[0047]

[0048] b. Determine the positive and negative ideal solutions: Positive ideal solution It is the optimal value of each indicator, that is, the maximum value after weighted standardization, the negative ideal solution. It is the worst value of each indicator, that is, the minimum value after weighted standardization:

[0049]

[0050]

[0051] c. Calculate the Euclidean distance: Calculate the Euclidean distance from each point to the positive and negative ideal solutions:

[0052]

[0053]

[0054] c. Calculate proximity and sort: Calculate the proximity of each carbon emission point. This reflects the degree of closeness between the corresponding carbon emission point and the ideal solution. The larger the value, the higher the carbon reduction priority of the corresponding carbon emission point.

[0055]

[0056] d. Priority sorting:

[0057] according to By ranking all carbon emission points from largest to smallest, the optimal carbon reduction strategy can be obtained.

[0058] According to the second aspect, one embodiment provides a carbon reduction system for urban rail vehicle depots based on the entropy weight method-TOPSIS, the system comprising:

[0059] The carbon emission point identification module is used to identify carbon emission points in each functional zone of the urban rail vehicle depot.

[0060] The evaluation index system construction module is used to comprehensively consider multiple dimensions, including emission scale, carbon reduction potential, economic cost, investment return, and implementation difficulty, to construct a multi-dimensional carbon emission point carbon reduction priority evaluation index system.

[0061] The carbon reduction priority ranking module is used to calculate the weight of each evaluation indicator based on the various evaluation indicators of each carbon emission point, and combine the TOPSIS method to rank the carbon reduction priorities of each carbon emission point.

[0062] This invention provides a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS, which has the following beneficial effects:

[0063] (1) The system has completed the detailed identification of carbon emission points in all aspects of the vehicle base and clarified the core contribution areas of carbon emissions. This invention divides the vehicle base into five functional areas according to functional zoning, and identifies a total of 23 carbon emission points covering all aspects of production, operation and maintenance, office, and auxiliary processes, achieving comprehensive coverage of carbon emissions in the vehicle base. The calculation results show that the annual carbon emissions of a typical vehicle base can reach 5,817 tons, of which the vehicle operation and maintenance area is the core contribution area of ​​carbon emissions, accounting for more than 50%, and the running gear maintenance equipment and train operation and maintenance equipment are the core emission sources with the largest emission scale in a single point.

[0064] (2) A multi-dimensional carbon reduction priority evaluation system was constructed, which solved the problem of subjective bias in traditional carbon reduction decision-making. This invention starts from five core dimensions: emission scale, carbon reduction potential, economic cost, investment return, and implementation difficulty. It establishes an evaluation index system that takes into account both emission reduction benefits and feasibility of implementation. The entropy weight method is used to objectively determine the index weights. Combined with the TOPSIS method, the carbon reduction priority of each location is quantitatively ranked, avoiding the decision-making bias caused by traditional subjective weighting methods and providing an objective quantitative tool for carbon reduction decision-making.

[0065] (3) The effectiveness of the evaluation model was verified through typical case studies, and the core objectives for carbon reduction at vehicle bases were clarified. The case study analysis based on actual data from typical vehicle bases showed that the model can effectively identify high-priority carbon reduction sites with great potential, good economic efficiency, and easy implementation. This provides a clear direction for operating units to accurately allocate carbon reduction resources and prioritize the technological transformation of core sites, effectively improving the input-output efficiency of carbon reduction work.

[0066] (4) The results of this invention can provide important decision-making support for carbon reduction efforts in the urban rail transit industry. Compared with traditional macro-level carbon reduction strategies, the refined carbon emission identification and prioritization method proposed in this invention can help operating units shift from a "broad-based" to a "precision-based" carbon reduction model. It can not only effectively tap the carbon reduction potential of vehicle depots, but also provide a research paradigm that can be referenced for carbon reduction efforts in other similar transportation infrastructures, thus contributing to the achievement of the dual carbon goals of the entire transportation industry. Attached Figure Description

[0067] Figure 1 A flowchart illustrating a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS, provided as an embodiment of the present invention;

[0068] Figure 2 A comparison chart of carbon emissions from different functional zones of an urban rail vehicle depot in an embodiment of the present invention, provided by a method for reducing carbon emissions in urban rail vehicle depots based on the entropy weight method-TOPSIS.

[0069] Figure 3 This is a comparison chart of carbon emissions at various emission points in an urban rail vehicle depot based on the entropy weight method-TOPSIS, provided as an embodiment of the present invention. Detailed Implementation

[0070] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of the invention. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to the present invention are not shown or described in the specification. This is to avoid obscuring the core parts of the invention with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0071] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0072] The first embodiment of this invention provides a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS. The following is a combination of... Figure 1 Please provide a detailed explanation.

[0073] like Figure 1 As shown, in step S100, carbon emission points are identified for each functional zone according to the functional zones of the urban rail vehicle depot.

[0074] The above steps specifically include:

[0075] In this embodiment, according to the functional zoning of the vehicle base, all carbon emission point systems are divided into five categories, and a total of 23 specific carbon emission points are identified, achieving full coverage of the entire area and all aspects of the vehicle base.

[0076] 1.1 Acquisition of carbon emission points at vehicle bases

[0077] 1.1.1 Carbon emission points in vehicle operation and maintenance work areas

[0078] The vehicle operation and maintenance area is the core production area of ​​the vehicle base and also the area with the highest concentration of energy consumption and carbon emissions. A total of 8 key carbon emission points were identified:

[0079] (1) Train operation and maintenance equipment emission points: corresponding to the vehicle depot operation warehouse, overhaul warehouse, car body maintenance warehouse, static adjustment warehouse, purging warehouse, etc. Mainly includes the power consumption emissions of equipment such as fixed car lifting machines, car moving platforms, static adjustment power cabinets, purging, and car body weighing systems.

[0080] (2) Emission points for running gear maintenance equipment: corresponding to the wheel turning warehouse, dynamic inspection shed, and wheel and bogie maintenance workshop of the vehicle base. This includes the power consumption emissions of maintenance equipment such as wheel turning lathes, dynamic wheel size inspection equipment, bogie tilting maintenance bench, wheelset flaw detector, wheel lathe, wheelset running-in test bench, and bogie static load test bench.

[0081] (3) Vehicle component maintenance emission points: corresponding to the vehicle base dynamic testing shed, overhaul depot pantograph and air conditioning maintenance room. This includes the automatic pantograph testing equipment and the power consumption emissions required for pantograph and air conditioning system maintenance.

[0082] (4) Under-vehicle component maintenance and discharge points: corresponding to the vehicle base hook and buffer, motor, brake, inverter and circuit breaker maintenance rooms, including the power consumption emissions required for the maintenance of the above equipment.

[0083] (5) Vehicle body paint drying emission point: corresponding to the vehicle body paint drying warehouse of the vehicle base. It mainly includes the power consumption emissions of the paint drying equipment and the process emissions of paint solvent evaporation.

[0084] (6) Vehicle washing emission point: corresponding to the vehicle base car wash garage. It mainly includes the indirect emissions from electricity consumption and water consumption during car washing in the car wash garage.

[0085] (7) Emission points of lifting and transport equipment: Indirect emissions of electricity consumption and fuel consumption of lifting and transport equipment, handling vehicles, and shunting locomotives in each warehouse of the vehicle base.

[0086] (8) Emission points for warehouse ventilation and dust removal, lighting and sockets: corresponding to the power consumption emissions of each workshop's dust removal system, fresh air system fan, warehouse lighting and sockets.

[0087] 1.1.2 Carbon emission points in the power plant

[0088] The power plant is the base's energy hub, undertaking core functions such as power transformation and distribution, and supply of cooling and heating sources. A total of 6 carbon emission points were identified:

[0089] (1) Transformer loss emission points: the indirect power emission caused by iron loss and copper loss of the main transformer and box-type transformer.

[0090] (2) Chiller unit discharge point: corresponding to the power consumption discharge of the central air conditioning chiller unit.

[0091] (3) Heat pump unit emission point: the power consumption emission of the corresponding heating / cooling heat pump unit.

[0092] (4) Fire pump set discharge point: corresponds to the power consumption discharge of the fire pump during fire emergency drills.

[0093] (5) Air compressor discharge point: corresponding to the power consumption discharge of the air compressor.

[0094] (6) Discharge point of reactive power compensation device: the discharge of the reactive power compensation device itself and the energy consumption of operation.

[0095] 1.1.3 Carbon emission sites in office and living areas

[0096] The office and living area serves as the base's logistical support area, encompassing all aspects of personnel's work and life. A total of 5 carbon emission points were identified:

[0097] (1) Office equipment emission points: corresponding to the power consumption emissions of office equipment such as computers, printers, and servers.

[0098] (2) Air conditioning emission points in living areas: power consumption emissions from air conditioning equipment in office areas, dormitories and canteens.

[0099] (3) Lighting emission points in living areas: power consumption emissions from lighting equipment in office areas, dormitories, and canteens.

[0100] (4) Gas emission point in the canteen: Direct emissions from the combustion of natural gas fuel in the canteen stoves.

[0101] (5) Domestic hot water discharge point: corresponding to the energy consumption discharge of electric water heaters and gas water heaters.

[0102] 1.1.4 Carbon emission points in outdoor work areas

[0103] (1) The outdoor work area covers the outdoor work and access links of the base, and a total of 2 carbon emission points were identified:

[0104] (2) Outdoor lighting emission points: the power consumption emissions of streetlights and site lighting in the corresponding area.

[0105] (3) Outdoor work equipment emission points: corresponding site flushing pumps, charging piles and other outdoor work equipment energy consumption emissions.

[0106] 1.1.5 Carbon emission points of auxiliary facilities

[0107] (1) Ancillary facilities are supplementary facilities to ensure the normal operation of the base. A total of 2 carbon emission sites were identified:

[0108] (2) Wastewater treatment discharge point: the power consumption of equipment such as aeration blowers and booster pumps in the corresponding wastewater treatment plant.

[0109] (3) Security and communication emission points: power consumption emissions of equipment such as surveillance cameras, access control systems, and communication switches.

[0110] 1.2 Emission Source Analysis

[0111] The sources of emissions at all locations are divided into two main categories: "direct emissions" and "indirect emissions."

[0112] 1.2.1 Direct emissions

[0113] This refers to emissions generated from fuel combustion and process emissions within the vehicle depot. Specifically, it includes: fuel combustion emissions from standby diesel generators; gas combustion emissions from natural gas stoves in the canteen; fuel combustion emissions from fuel-powered forklifts; and CO2 emissions from the volatilization and conversion of organic solvents during painting operations.

[0114] 1.2.2 Indirect emissions

[0115] This refers to the emissions generated during the production process of purchased electricity consumed by the vehicle depot, which is the most critical source of emissions for urban rail vehicle depots. The energy consumption of all electrical equipment is converted into indirect carbon emissions for the depot through grid emission factors.

[0116] 1.3 Carbon Emission Intensity Calculation

[0117] The formula for calculating carbon emission intensity is as follows:

[0118] (1)

[0119] in:

[0120] Total carbon emissions (tCO2);

[0121] For activity data of direct emission sources (such as fuel consumption in tons, gas consumption in cubic meters).

[0122] For direct emission sources, the recommended values ​​in the "Guidelines for Greenhouse Gas Emissions Accounting and Reporting" are adopted: 3.16 tCO2 / t for diesel and 2.18 kgCO2 / m³ for natural gas.

[0123] For indirect emission sources, the activity data (i.e., electricity consumption in MWh).

[0124] The emission factor is the average value of the regional power grid baseline emission factor in my country in 2023, which is 0.581 tCO2 / MWh.

[0125] Based on the vehicle depot designed and already in operation by our institute, the annual carbon emissions of each core location are shown in the table below, obtained through data collection and calculation.

[0126] Table 1. Calculation of Annual Carbon Emissions from Vehicle Base

[0127]

[0128] According to Table 1, Figure 2 and Figure 3 It is known that the annual carbon emissions of the vehicle depot reached 5,817 tons. Among the various functional areas of the vehicle depot, the "vehicle operation and maintenance area" has the largest annual carbon emissions, which also reflects that the vehicle depot is a place where vehicle operation and maintenance are the core businesses. Analyzing the carbon emission points, the "running section maintenance equipment emission point" has the largest annual carbon emissions, reaching 885 tons. Other points with annual carbon emissions exceeding 500 tons include the "train operation and maintenance equipment emission point" and the "undercarriage component maintenance emission point".

[0129] like Figure 1 As shown, in step S200, a multi-dimensional carbon emission point carbon reduction priority evaluation index system is constructed by comprehensively considering multiple dimensions including emission scale, carbon reduction potential, economic cost, investment return, and implementation difficulty.

[0130] In this embodiment, in order to accurately target the core objectives of carbon reduction efforts and avoid resource dispersion, relevant strategies can be established to identify the core locations with the greatest carbon reduction potential and the highest input-output ratio.

[0131] Therefore, this embodiment selects five core elements for carbon reduction in vehicle bases, mainly derived from three dimensions: emission scale, carbon reduction potential, and economy. The five core factors are as follows:

[0132] (1) Annual carbon emissions: Reflects the emission scale of the site. The larger the emissions, the higher the marginal benefit of carbon reduction.

[0133] (2) Technological carbon reduction potential: Technological carbon reduction potential refers to the proportion of carbon emission reduction that can be achieved through technological means such as energy-saving renovation, replacement of high-efficiency equipment, and intelligent control. It is calculated by the ratio of the difference in carbon emissions before and after the renovation to the emissions before the renovation. It reflects the maximum carbon reduction that can be achieved at this site through technological renovation and management optimization. The greater the potential, the greater the emission reduction space.

[0134] (3) Unit carbon reduction investment cost: The unit carbon reduction investment cost is the ratio of the total investment of the project to the annual carbon emission reduction. It reflects the fixed asset investment required to reduce CO2 emissions by 1 ton and is the core indicator for evaluating the economic efficiency of the transformation. The lower the carbon reduction cost, the better the economic efficiency.

[0135] (4) Investment recovery period: The investment recovery period is calculated using the static recovery period, which is the ratio of the total investment of the project to the annual energy-saving benefits, reflecting the number of years required for the investment in the renovation to be recovered through energy-saving benefits. The shorter the recovery period, the higher the financial feasibility of the project.

[0136] (5) Implementation difficulty: This reflects the difficulty of implementing the technological transformation, including its impact on operations and the maturity of the technology. The lower the difficulty, the easier it is to implement. The implementation difficulty is rated from 1 to 5, with a higher value indicating greater difficulty.

[0137] like Figure 1 As shown, in step S300, based on the various evaluation indicators of each carbon emission point, the weight of each evaluation indicator is calculated using the entropy weight method, and the carbon reduction priority of each carbon emission point is ranked by combining the TOPSIS method.

[0138] This embodiment uses TOPSIS (Topology for Ideal Solution Ranking) combined with entropy weighting for ranking. TOPSIS is a commonly used multi-attribute decision-making method that can objectively rank schemes by calculating the distance between each scheme and the positive and negative ideal solutions. Entropy weighting is used to objectively determine the weights of each indicator, avoiding the bias of subjective weighting. The specific steps are as follows:

[0139] Step 310: Construct the initial decision matrix

[0140] An initial decision matrix is ​​constructed based on five core factors at 23 carbon emission sites:

[0141] (2)

[0142] In the formula:

[0143] n=23 represents the number of carbon emission sites sampled.

[0144] m=5 represents the number of core factors (indicators);

[0145] For the first The first carbon emission point The original values ​​of each factor (indicator).

[0146] Step S320: Indicator Standardization Processing

[0147] Because different indicators have different dimensions and magnitudes, they need to be standardized to eliminate the influence of dimensions. This embodiment divides the indicators into positive indicators (higher values ​​are better, including annual carbon emissions and technological carbon reduction potential) and negative indicators (lower values ​​are better, including unit carbon reduction investment cost, investment payback period, and implementation difficulty), each using different standardization formulas:

[0148] Standardization of positive indicators:

[0149] (3)

[0150] Standardization of negative indicators:

[0151] (4)

[0152] After standardization, the standardized matrix is ​​obtained. All indicator values ​​are mapped to Interval.

[0153] Step S330: Calculate index weights using the entropy weight method

[0154] The objective weights of each indicator are calculated using information entropy theory. The specific calculation process is as follows:

[0155] (1) Calculate the first Under this indicator, the first The weighting of indicators at each point:

[0156] (5)

[0157] (2) Calculate the first Information entropy of the indicator:

[0158] (6)

[0159] in For standardized coefficients, ensure .like Then define .

[0160] (3) Calculate the first Coefficient of variation of the indicators:

[0161] (7)

[0162] The larger the difference coefficient, the greater the amount of effective information provided by the indicator, and the higher its weight should be.

[0163] (4) Calculate the indicator weights:

[0164] (8)

[0165] Step S340: TOPSIS Prioritization

[0166] (1) Constructing the weighted standardization matrix: Multiply the standardization matrix by the index weights to obtain the weighted standardization matrix. :

[0167] (9)

[0168] (2) Determine the positive and negative ideal solutions: positive ideal solution It is the optimal value of each indicator (i.e., the maximum value after weighted standardization), the negative ideal solution. These are the worst values ​​(i.e., the minimum values ​​after weighted standardization) for each indicator:

[0169] (10)

[0170] (11)

[0171] (3) Calculate the Euclidean distance: Calculate the Euclidean distance from each point to the positive ideal solution and the negative ideal solution:

[0172] (12)

[0173] (13)

[0174] (4) Calculate proximity and sort: Calculate the proximity of each point. This reflects how close the point is to the ideal solution. The larger the value, the higher the priority for carbon reduction at that location.

[0175] (14)

[0176] Step S350: Priority sorting

[0177] according to Sort all locations from largest to smallest to obtain the optimal carbon reduction strategy.

[0178] Example Analysis:

[0179] The specific data (initial matrix) of the five evaluation indicators based on 23 carbon emission sites in the typical base are shown in the table below.

[0180] Table 2 Data on 5 Influencing Factors of Carbon Emission Points at Vehicle Depots

[0181]

[0182] The data after standardization is shown in Table 3.

[0183] Table 3 Data Standardization

[0184]

[0185] The data were subjected to entropy weighting and index weighting calculations, and the results are shown in Table 4.

[0186] Table 4. Entropy weight method for calculating index weights

[0187]

[0188] Finally, the carbon reduction priorities for each emission point at the vehicle base were ranked, as shown in Table 5.

[0189] Table 5. Priority Ranking of Carbon Reduction at Each Emission Point in the Vehicle Base

[0190]

[0191] Corresponding to the aforementioned carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS, this invention also discloses a carbon reduction system for urban rail vehicle depots based on the entropy weight method-TOPSIS, which specifically includes:

[0192] The carbon emission point identification module is used to identify carbon emission points in each functional zone of the urban rail vehicle depot.

[0193] The evaluation index system construction module is used to comprehensively consider multiple dimensions, including emission scale, carbon reduction potential, economic cost, investment return, and implementation difficulty, to construct a multi-dimensional carbon emission point carbon reduction priority evaluation index system.

[0194] The carbon reduction priority ranking module is used to calculate the weight of each evaluation indicator based on the various evaluation indicators of each carbon emission point, and combine the TOPSIS method to rank the carbon reduction priorities of each carbon emission point.

[0195] It should be noted that for a detailed description of the carbon reduction system for urban rail vehicle depots based on the entropy weight method-TOPSIS provided in the embodiments of the present invention, please refer to the relevant description of the carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS provided in the embodiments of the present invention, which will not be repeated here.

[0196] In addition, embodiments of the present invention also provide an electronic device, the device comprising: a processor and a memory; the memory being used to store one or more program instructions; the processor being used to execute one or more program instructions to perform the steps of a carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in any of the preceding embodiments.

[0197] It should be noted that for a detailed description of an electronic device provided in the embodiments of the present invention, please refer to the relevant description of a carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS provided in the embodiments of this application, which will not be repeated here.

[0198] In addition, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in any of the preceding claims.

[0199] It should be noted that for a detailed description of the computer-readable storage medium provided in the embodiments of the present invention, please refer to the relevant description of the carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS provided in the embodiments of this application, which will not be repeated here.

[0200] Those skilled in the art will understand that all or part of the functions of the various methods in the above embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, which may include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to achieve the above functions. For example, the program can be stored in the memory of a device, and when the program in the memory is executed by the processor, all or part of the above functions can be achieved. In addition, when all or part of the functions in the above embodiments are implemented by computer programs, the program can also be stored in a server, another computer, disk, optical disk, flash drive, or external hard drive, etc., and can be downloaded or copied to the memory of a local device, or the system of the local device can be updated. When the program in the memory is executed by the processor, all or part of the functions in the above embodiments can be achieved.

[0201] The above examples illustrate the present invention only to aid in understanding it and are not intended to limit the scope of the invention. Those skilled in the art can make various simple deductions, modifications, or substitutions based on the principles of this invention.

Claims

1. A carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS, characterized in that, The method includes: Based on the functional zoning of the urban rail vehicle depot, carbon emission points are identified for each functional zone. Taking into account multiple dimensions including emission scale, carbon reduction potential, economic cost, return on investment, and implementation difficulty, a multi-dimensional evaluation index system for carbon emission point carbon reduction priority is constructed. Based on the various evaluation indicators of each carbon emission point, the entropy weight method is used to calculate the weight of each evaluation indicator, and the TOPSIS method is combined to rank the carbon reduction priorities of each carbon emission point.

2. The carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in claim 1, characterized in that, Based on the functional zoning of the urban rail vehicle depot, carbon emission points are identified for each functional zone, specifically including: The functional zones of an urban rail vehicle depot include a vehicle operation and maintenance area, a power room, an office and living area, an outdoor work area, and auxiliary facilities. Carbon emission points in the vehicle operation and maintenance work area include emission points from train operation / maintenance equipment, emission points from running gear maintenance equipment, emission points from onboard component maintenance, emission points from underboard component maintenance, emission points from car body painting and drying, emission points from car body cleaning, emission points from lifting and transportation equipment, and emission points from warehouse ventilation and dust removal, lighting, and sockets. Carbon emission points in the power room include transformer loss emission points, chiller unit emission points, heat pump unit emission points, fire pump unit emission points, air compressor emission points, and reactive power compensation device emission points. Carbon emission points in the office and living area include emission points from office equipment, air conditioning in the living area, lighting in the living area, gas emission points in the canteen, and domestic hot water emission points. Carbon emission points in outdoor work areas include outdoor lighting emission points and outdoor work equipment emission points; Carbon emission points for ancillary facilities include wastewater treatment discharge points and security and communication emission points.

3. The carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in claim 1, characterized in that, Based on the functional zoning of the urban rail vehicle depot, carbon emission points are identified for each functional zone, specifically including: The emission sources of all carbon emission points are divided into two categories: direct emissions and indirect emissions. The annual carbon emissions and carbon emission intensity of carbon emission points are calculated according to the emission source classification.

4. The carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in claim 1, characterized in that, Taking into account multiple dimensions including emission scale, carbon reduction potential, economic cost, return on investment, and implementation difficulty, a multi-dimensional evaluation index system for prioritizing carbon reduction at carbon emission points is constructed, specifically including: The carbon emission point carbon reduction priority evaluation index system includes annual carbon emissions, carbon reduction potential through technology, unit carbon reduction investment cost, investment payback period, and implementation difficulty.

5. The carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in claim 1, characterized in that, The entropy weight method is used to calculate the weights of each evaluation index, specifically including: a. Construct the initial decision matrix: Where: n is the number of carbon emission point samples; m is the number of evaluation indicators; For the first The first carbon emission point The original values ​​of each evaluation indicator; b. Standardization of indicators, resulting in a standardized matrix. All indicator values ​​are mapped to interval; c. Calculating index weights using the entropy weight method: The objective weights of each indicator are calculated using information entropy theory. The specific calculation process is as follows: Calculate the first Under the evaluation indicators, the first The proportion of indicators for each carbon emission point : Calculate the first Information entropy of the indicator : in For standardized coefficients, ensure ;like Then define ; Calculate the first Coefficient of difference of the items : Calculate indicator weights : 。 6. The carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in claim 5, characterized in that, Indicator standardization processing specifically includes: The indicators are divided into positive and negative indicators, and different standardization formulas are used for each: Standardization of positive indicators: Standardization of negative indicators: 。 7. The carbon reduction method for urban rail vehicle depots based on entropy weight method-TOPSIS as described in claim 1, characterized in that, The TOPSIS method is used to prioritize carbon reduction efforts at each emission point, specifically including: a. Constructing a weighted standardized matrix: Multiplying the standardized matrix by the indicator weights yields the weighted standardized matrix. : b. Determine the positive and negative ideal solutions: Positive ideal solution It is the optimal value of each indicator, that is, the maximum value after weighted standardization, the negative ideal solution. It is the worst value of each indicator, that is, the minimum value after weighted standardization: c. Calculate the Euclidean distance: Calculate the Euclidean distance from each point to the positive and negative ideal solutions: c. Calculate proximity and sort: Calculate the proximity of each carbon emission point. This reflects the degree of closeness between the corresponding carbon emission point and the ideal solution. The larger the value, the higher the carbon reduction priority of the corresponding carbon emission point. d. Priority sorting: according to By ranking all carbon emission points from largest to smallest, the optimal carbon reduction strategy can be obtained.

8. A carbon reduction system for urban rail vehicle depots based on the entropy weight method-TOPSIS, characterized in that, The system includes: The carbon emission point identification module is used to identify carbon emission points in each functional zone of the urban rail vehicle depot. The evaluation index system construction module is used to comprehensively consider multiple dimensions, including emission scale, carbon reduction potential, economic cost, investment return, and implementation difficulty, to construct a multi-dimensional carbon emission point carbon reduction priority evaluation index system. The carbon reduction priority ranking module is used to calculate the weight of each evaluation indicator based on the various evaluation indicators of each carbon emission point, and combine the TOPSIS method to rank the carbon reduction priorities of each carbon emission point.

9. An electronic device, characterized in that, The device includes: a processor and a memory; The memory is used to store one or more program instructions; The processor is configured to run one or more program instructions to perform the steps of a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of a carbon reduction method for urban rail vehicle depots based on the entropy weight method-TOPSIS as described in any one of claims 1 to 7.

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