A method and system for evaluating carbon reduction performance of a railway construction process

Abstract

The application discloses a kind of railway construction construction process's carbon reduction performance evaluation method and system, belong to carbon emission control technical field, this method includes: based on project list determines the planned consumption of each consumption factor, consumption factor includes power consumption and energy consumption;Railway construction route is divided into multiple construction intervals, the planned emission of each construction interval is calculated;The actual emission of each consumption factor is obtained;After the first number of construction intervals, the first sequence is generated based on the planned emission of each construction interval, the second sequence is generated based on the actual emission, the first sequence and the second sequence are analyzed to determine the carbon reduction measures;After implementing the carbon reduction measures and after the second number of construction intervals, the actual emission of the construction interval after implementing the carbon reduction measures is obtained, and the corresponding planned emission is compared to evaluate the carbon reduction measures.The application effectively solves the problem of dynamic adjustment and effect evaluation of carbon reduction measures with long construction period and large span of railway construction.

Description

Technical Field

[0001] This invention belongs to the field of carbon emission control technology, specifically relating to a method and system for evaluating carbon reduction performance during railway construction. Background Technology

[0002] Railway construction involves the extensive use of energy-intensive materials such as concrete and steel, whose production processes generate significant carbon emissions. Additionally, fuel consumption in machinery and the use of air conditioning in offices and dormitories also contribute to carbon emissions. Current key measures to reduce carbon emissions include developing optimized plans before construction to reduce material usage, adopting low-carbon and environmentally friendly materials, and promoting energy-saving technologies and clean energy power equipment for machinery. In terms of evaluation methods, a life-cycle perspective is often used to statistically analyze energy consumption and carbon emissions during the construction phase, combining quantitative data with qualitative analysis to assess the effectiveness of carbon reduction measures.

[0003] For example, Chinese patent document CN118364986A discloses a quantitative evaluation method for low-carbon construction level in engineering construction process. This method is based on the carbon emissions generated in each construction stage, statistically analyzes the carbon emissions of building material production, construction machinery, and transportation with different parameters, calculates the carbon emission ratio of application and transportation corresponding to different parameters, and compares the calculated values ​​of carbon emission ratio of application and transportation corresponding to different parameters with the corresponding evaluation values ​​of carbon emission ratio of application and transportation, thereby evaluating the carbon emissions of the construction stage of building engineering.

[0004] However, railway construction projects are characterized by long construction periods and wide geographical spans. Therefore, carbon reduction measures can be dynamically set according to the actual situation during the construction process to improve the carbon reduction effect. However, existing technologies do not provide specific evaluation methods for evaluating the dynamically set carbon reduction measures during railway construction. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a method and system for evaluating carbon reduction performance during railway construction, thereby resolving the issues present in the background art.

[0006] To achieve the aforementioned objectives, this invention proposes a method for evaluating carbon reduction performance during railway construction, comprising:

[0007] Obtain a project list, and determine the planned consumption of each consumption factor based on the project list, wherein the consumption factors include electricity consumption and energy consumption;

[0008] Set a unit emission factor for each of the consumption factors, divide the railway construction route into multiple construction sections, and calculate the planned emission amount for each of the construction sections based on the planned consumption amount and the unit emission factor;

[0009] A monitoring device is installed at the construction site of the construction section. After the construction section is completed, the actual consumption of each of the consumption factors is obtained based on the monitoring device, and the actual emission is calculated based on the actual consumption and the unit emission factor.

[0010] After a first number of construction intervals, a first sequence is generated based on the planned emissions of each construction interval, and a second sequence is generated based on the actual emissions. The first sequence and the second sequence are analyzed to determine carbon reduction measures.

[0011] After implementing carbon reduction measures and passing through a second number of the construction sections, the actual emissions of the construction sections after implementing carbon reduction measures are obtained and compared with the corresponding planned emissions to evaluate the effectiveness of the carbon reduction measures.

[0012] Furthermore, obtaining the actual consumption amount of each consumption factor based on the monitoring device includes the following steps:

[0013] The monitoring device includes power sensors and monitoring cameras. The construction area within the construction zone is divided into multiple independent areas. Power sensors are installed in each independent area. The power sensors count the electricity consumption of each independent area and generate a historical electricity consumption sequence for each independent area based on the electricity consumption. After the construction in the construction zone is completed, the historical electricity consumption sequence is summarized to generate a total electricity consumption. The total electricity consumption is multiplied by the corresponding unit emission factor to obtain the actual emission amount of the electricity consumption.

[0014] The surveillance camera is installed at the entrance of the construction area. Based on the surveillance video recorded by the surveillance camera, the surveillance video is analyzed based on the image recognition algorithm to obtain the type of machinery and equipment entering the site each day, the corresponding number of machines entering the site, and the dwell time of each machine. The unit energy consumption of each type of machinery and equipment is set. The total consumption is calculated based on the number of machines entering the site, the dwell time, and the unit energy consumption. The total consumption is multiplied by the corresponding unit emission factor to obtain the actual emission of the energy used.

[0015] Further, analyzing the first and second sequences to determine carbon reduction measures includes the following steps:

[0016] Both the first sequence and the second sequence include an electricity emission sequence corresponding to the electricity consumption and an energy emission sequence corresponding to the energy consumption. A first difference sequence is generated based on the electricity emission sequence included in the first sequence and the energy emission sequence included in the second sequence, and a second difference sequence is generated. A first average value of the first difference sequence and a second average value of the second difference sequence are calculated. A first threshold and a second threshold are set. If the first average value is greater than the first threshold, an electricity carbon reduction measure is generated. If the second average value is greater than the second threshold, an energy carbon reduction measure is generated.

[0017] Furthermore, carbon reduction measures for generating electricity include the following steps:

[0018] Multiple standard carbon reduction measures are preset, and multiple energy-saving modes are set for each type of power equipment. The standard carbon reduction measures include the selection strategy of the energy-saving mode for each type of power equipment. Each standard carbon reduction measure has a corresponding numerical range. The difference between the first average value and the first threshold is calculated. Based on the numerical range in which the difference is located, the corresponding standard carbon reduction measure is selected as the power carbon reduction measure. The independent region that serves as the target for the power carbon reduction measure is determined and defined as the target region. The amount of electricity consumption reduction in each target region is determined. Based on the historical execution records of the standard carbon reduction measures, the probability of power equipment being manually changed after being adjusted to various energy-saving modes is calculated. The combination of various energy-saving modes of power equipment that meets the amount of electricity consumption reduction is selected as the first combination.

[0019] The selection strategy includes maximizing energy saving value and minimizing modification probability. Based on the selection strategy, a combination is selected from the first combination as the second combination. The operating mode of the power equipment in the independent area is adjusted according to the second combination to implement power carbon reduction measures.

[0020] Further, determining the electricity consumption reduction for each target area includes the following steps:

[0021] The planned electricity consumption of the construction area is decomposed into daily restricted electricity consumption. Based on the historical electricity consumption sequence of each independent area, the restricted electricity consumption is further divided into regional electricity consumption. A switching time point is set daily. The actual electricity consumption sequence of each independent area before the switching time point is obtained by power sensors. The predicted electricity consumption sequence from the switching time point to the end of the day is predicted. Based on the predicted electricity consumption sequence and the actual electricity consumption sequence, the cumulative electricity consumption of each independent area is calculated. The difference between the cumulative electricity consumption and the regional electricity consumption is used as the electricity consumption reduction amount.

[0022] Furthermore, predicting the forecasted electricity consumption sequence from the switching time point to the end of the day includes the following steps:

[0023] The process involves obtaining multiple actual electricity consumption sequences of different time lengths prior to the switching time point as a first sequence, extracting a second sequence from the historical electricity consumption sequence that has the same time length as each of the first sequences, selecting multiple second sequences with the highest similarity to each of the first sequences as a third sequence, obtaining a fourth sequence from the historical electricity consumption sequence that is after the third sequence and has the same length as the predicted electricity consumption sequence, clustering the fourth sequence to obtain multiple groups, selecting the group that includes the most fourth sequences as the target group, and selecting one of the fourth sequences from the target group as the predicted electricity consumption sequence.

[0024] Furthermore, energy generation and carbon reduction measures include the following steps:

[0025] Calculate the second difference between the second average value and the second threshold. Based on the second difference, construct a consumption reduction function and a cost increase function for replacing fuel-powered machinery with new energy machinery. Solve the consumption reduction function and the cost increase function to obtain energy carbon reduction measures. The energy carbon reduction measures include the number of replacements of fuel-powered machinery with new energy machinery. Change the machinery based on the number of replacements to implement the energy carbon reduction measures.

[0026] This invention also provides a carbon reduction performance evaluation system for railway construction processes. This system is used to implement the methods described above, and includes:

[0027] The planning module obtains a project list and determines the planned consumption amount for each consumption factor based on the project list. The consumption factors include electricity consumption and energy consumption.

[0028] The calculation module sets the unit emission factor for each of the consumption factors, divides the railway construction route into multiple construction sections, and calculates the planned emission amount for each construction section based on the planned consumption amount and the unit emission factor;

[0029] The accounting module sets up a monitoring device at the construction site of the construction section. After the construction section is completed, it obtains the actual consumption of each of the consumption factors based on the monitoring device, and calculates the actual emission based on the actual consumption and the unit emission factor.

[0030] The generation module generates a first sequence based on the planned emissions of each construction interval after passing through a first number of construction intervals, generates a second sequence based on the actual emissions, and analyzes the first sequence and the second sequence to determine carbon reduction measures.

[0031] The comparison module, after implementing carbon reduction measures and passing through a second number of the construction sections, obtains the actual emissions of the construction sections after implementing carbon reduction measures, and compares them with the corresponding planned emissions to evaluate the effectiveness of the carbon reduction measures.

[0032] Beneficial effects: This invention combines electricity consumption, energy consumption, and planned emissions per unit emission factor for construction zones, and obtains actual consumption in real time through on-site monitoring devices. Based on the planned and actual emissions of multiple construction zones, a sequence is generated and analyzed, which can systematically identify carbon emission deviations and assist in the formulation of effective carbon reduction measures. Finally, the implementation effect of carbon reduction measures is evaluated by comparing actual emissions with planned emissions, effectively solving the problem of dynamic adjustment and effect evaluation of carbon reduction measures in railway construction with long cycles and large spans. Attached Figure Description

[0033] Figure 1 This invention provides a flowchart of the steps for evaluating the carbon reduction performance of railway construction processes.

[0034] Figure 2 This is a schematic diagram of the structure of a carbon reduction performance evaluation system for railway construction process according to the present invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0036] It is understood that the terms "first," "second," etc., used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of this application, a first script may be referred to as a second script, and similarly, a second script may be referred to as a first script.

[0037] like Figure 1 As shown, a method for evaluating carbon reduction performance during railway construction includes:

[0038] S1: Obtain the project list and determine the planned consumption of each consumption factor based on the project list. Consumption factors include electricity consumption and energy consumption.

[0039] S2: Set the unit emission factor for each consumption factor, divide the railway construction route into multiple construction sections, and calculate the planned emission of each construction section based on the planned consumption and the unit emission factor.

[0040] First, the optimizable items in the construction process are identified. In this embodiment, the optimizable items include electricity consumption and energy consumption during construction. Electricity consumption is generated by air conditioning, lighting, and ventilation equipment during construction, while energy consumption is generated by construction equipment such as fuel-powered trucks, excavators, and road rollers used for transporting materials. Other influencing factors, such as carbon emissions from concrete and steel, are not considered as optimization targets because material changes during construction may affect construction quality and progress. Therefore, this embodiment only considers electricity consumption and energy consumption as optimization targets, that is, optimizing the carbon emissions of electrical equipment and construction machinery throughout the entire construction process.

[0041] The unit emission factor is determined according to the "New Quota for Railway Engineering Budget 2007", which includes the unit emissions of gasoline and diesel. The emissions from electricity consumption are determined based on the energy structure of power generation, for example, 30% fuel oil power generation, 30% coal power generation, 20% hydropower, and 20% wind power. Among them, the carbon emissions from fuel oil power generation are 0.657 kg / kWh, the carbon emissions from coal power generation are 0.858 kg / kWh, and hydropower and wind power do not produce carbon emissions, so their unit emission factor is set to 0. Therefore, the carbon emissions per kilowatt-hour are 0.657*0.3 + 0.858*0.3 = 0.4545 kg / kWh.

[0042] When dividing construction zones, construction zones have different types, such as roadbed type, tunnel type, and bridge type. The first sequence is then generated based on the planned emissions of construction zones of the same type.

[0043] In the early planning stage, the gasoline, diesel and electricity consumption of each construction section is determined. Then, the fuel consumption, diesel consumption, etc. are multiplied by the corresponding unit emission factor to obtain the planned emissions of energy consumption. The electricity consumption is multiplied by the unit emission factor of different power generation energy sources according to the proportion to obtain the planned emissions of electricity consumption.

[0044] S3: Set up monitoring devices at the construction site of the construction section. After the construction section is completed, obtain the actual consumption of each consumption factor based on the monitoring devices, and calculate the actual emission based on the actual consumption and the unit emission factor.

[0045] In this embodiment, obtaining the actual consumption of each consumption factor based on the monitoring device includes the following steps:

[0046] The monitoring device includes power sensors and surveillance cameras. The construction area within the construction zone is divided into multiple independent zones. Power sensors are installed in each independent zone. The power sensors count the electricity consumption of each independent zone and generate a historical electricity consumption sequence for each independent zone based on the electricity consumption. After the construction of the construction zone is completed, the historical electricity consumption sequence is summarized to generate the total electricity consumption. The total electricity consumption is multiplied by the corresponding unit emission factor to obtain the actual emission of electricity consumption.

[0047] Surveillance cameras are installed at the entrance of the construction area. The cameras record video of the construction area, and the video is analyzed using image recognition algorithms to obtain the types of machinery and equipment entering the site each day, the corresponding number of machines entering the site, and the dwell time of each machine. The unit energy consumption of each type of machinery and equipment is set, and the total consumption is calculated based on the number of machines entering the site, the dwell time, and the unit energy consumption. The total consumption is multiplied by the corresponding unit emission factor to obtain the actual energy emissions.

[0048] The construction area can be divided into multiple independent zones according to function. For example, accommodation, office, and entertainment areas can be divided into separate zones; each individual room can be divided into a separate zone; or connected building areas can be divided into separate zones; or a grid-based division method can be used based on the actual distribution. After division, power sensors (electricity meters with network connectivity) are installed in each independent zone. These meters record the hourly electricity consumption of each zone and compile the consumption data into historical electricity consumption sequences. After construction is completed in the construction area, the corresponding historical electricity consumption sequences are summed to obtain the total electricity consumption. Based on the previously described method and the composition of power generation energy, the total electricity consumption is multiplied by the corresponding unit emission factor to obtain the actual emissions.

[0049] The surveillance cameras are equipped with network capabilities. They upload recorded video footage to a cloud server. The cloud server uses image recognition algorithms to determine the type, quantity, and dwell time of machinery entering the construction area each day. Image recognition algorithms, such as convolutional neural networks (CNNs), are existing technologies for vehicle type identification and will not be discussed further here. The image recognition algorithm obtains the type and license plate number of the entering machinery based on the surveillance video. Machinery types include excavators, bulldozers, and road rollers. The dwell time is determined based on the entry and exit times of the license plates. The unit energy consumption of each type of machinery is pre-set. For example, if the unit energy consumption of an excavator is 15L of diesel per hour, and the total dwell time of all excavators of this type is 10 hours, then the total consumption is 15 * 10 = 150L. Multiplying 150L by the unit emission factor corresponding to diesel yields the diesel emission amount. Adding the emissions of diesel, gasoline, etc., gives the actual energy consumption emissions. In other embodiments, surveillance cameras can be installed on-site to analyze whether the mechanical equipment is in an active or stopped state through video analysis. The dwell time can be determined based on the duration of the mechanical equipment in an active state, thereby obtaining a more accurate mechanical running time.

[0050] S4: After the first number of construction intervals, a first sequence is generated based on the planned emissions of each construction interval, and a second sequence is generated based on the actual emissions. The first and second sequences are analyzed to determine carbon reduction measures.

[0051] S5: After implementing carbon reduction measures and passing through a second number of construction zones, obtain the actual emissions of the construction zones after implementing carbon reduction measures, and compare them with the corresponding planned emissions to evaluate the effectiveness of the carbon reduction measures.

[0052] For example, if the first quantity is 5, after traversing 5 construction sections of different roadbed types, the planned emissions from these 5 construction sections are combined into a first sequence, and the actual emissions from these 5 construction sections are used as a second sequence. The first sequence is in the form of [A1 A2 A3 A4 A5 B1 B2 B3 B4 B5], and the second sequence is in the form of [C1 C2 C3 C4 C5 D1 D2 D3 D4 D5]. Here, A1-A5 represent the planned emissions from electricity consumption in the 5 construction sections, B1-B5 represent the planned emissions from energy consumption in the 5 construction sections, C1-C5 represent the actual emissions from electricity consumption in the 5 construction sections, and D1-D5 represent the actual emissions from energy consumption in the 5 construction sections. If the actual emissions in the second sequence are significantly greater than the planned emissions in the first sequence, then the first and second sequences are analyzed to determine carbon reduction measures. The specific analysis method will be introduced later.

[0053] After determining the carbon reduction measures, these measures are applied during construction in subsequent construction sections to reduce carbon emissions during the construction process. In this embodiment, the second quantity is the same as the first quantity. That is, after applying the carbon reduction measures, the actual emissions of each construction section are obtained again after passing through five roadbed types of construction sections. At the same time, the corresponding planned emissions are also obtained. If the actual emissions are close to or less than the planned emissions, it indicates that the carbon reduction measures have a good carbon reduction effect. In this case, the carbon reduction measures continue to be implemented in subsequent construction sections. Otherwise, other methods are used to reduce carbon emissions.

[0054] This invention first determines electricity and energy consumption by obtaining a project list, then determines the unit emission factor and divides construction intervals, combining the planned emissions of each construction interval with the electricity and energy consumption and the unit emission factor. Actual consumption is acquired in real time through on-site monitoring devices. A sequence is generated based on the planned and actual emissions of multiple construction intervals and analyzed to systematically identify carbon emission deviations and assist in formulating effective carbon reduction measures. Finally, based on multiple construction intervals, the effectiveness of carbon reduction measures is evaluated by comparing actual emissions with planned emissions, achieving continuous improvement in carbon emissions during the construction process.

[0055] This invention effectively solves the problem of dynamically adjusting and evaluating the effects of carbon reduction measures in railway construction projects with long construction cycles and large spans by systematically collecting and analyzing data in stages and across multiple zones.

[0056] In this embodiment, analyzing the first and second sequences to determine carbon reduction measures includes the following steps:

[0057] Both the first sequence and the second sequence include an electricity emission sequence corresponding to electricity consumption and an energy emission sequence corresponding to energy consumption. A first difference sequence is generated based on the electricity emission sequence included in the first sequence and the energy emission sequence included in the second sequence, and a second difference sequence is generated based on the energy emission sequence included in the first sequence and the second difference sequence. A first average value of the first difference sequence and a second average value of the second difference sequence are calculated. A first threshold and a second threshold are set. If the first average value is greater than the first threshold, an electricity carbon reduction measure is generated. If the second average value is greater than the second threshold, an energy carbon reduction measure is generated.

[0058] As previously recorded, the first sequence is [A1 A2 A3 A4 A5 B1 B2 B3 B4 B5], and the second sequence is [C1 C2 C3 C4 C5 D1 D2 D3 D4 D5]. Therefore, the electricity emission sequences are A1-A5 and C1-C5, and the energy emission sequences are B1-B5 and D1-D5. The first difference sequence is [C1-A1 C2-A2 C3-A3 C4-A4 C5-A5], and the second difference sequence is [D1-C1 D2-C2 D3-C3 D4-C4]. [D5-C5] Then calculate the first average value of the first difference sequence and the second average value of the second difference sequence. If the first average value is greater than 0, it indicates that the actual electricity consumption exceeds the planned electricity consumption. If the excess value exceeds the first threshold (80 kg), then electricity carbon reduction measures need to be used to reduce electricity consumption. If the second average value is greater than 0, it indicates that the actual energy consumption exceeds the planned energy consumption. If the excess value exceeds the second threshold (120 kg), then energy carbon reduction measures need to be used to reduce energy consumption.

[0059] In this embodiment, the measures for generating electricity to reduce carbon emissions include the following steps:

[0060] Multiple standard carbon reduction measures are preset, and multiple energy-saving modes are set for each type of power equipment. The standard carbon reduction measures include the selection strategy for the energy-saving mode of each type of power equipment. Each standard carbon reduction measure has a corresponding numerical range. The difference between the first average value and the first threshold is calculated. Based on the numerical range of the difference, the corresponding standard carbon reduction measure is selected as the power carbon reduction measure. An independent region is determined as the target region for the implementation of the power carbon reduction measures. The amount of electricity consumption reduction in each target region is determined. Based on the historical execution records of the standard carbon reduction measures, the probability of power equipment being manually changed after being adjusted to various energy-saving modes is calculated. The combination of various power equipment energy-saving modes that meet the amount of electricity consumption reduction is selected as the first combination.

[0061] The selection strategy includes maximizing energy savings and minimizing the probability of modification. Based on the selection strategy, a combination is selected from the first combination as the second combination. The operating mode of the power equipment in the independent area is adjusted according to the second combination to implement power carbon reduction measures.

[0062] Assuming the electrical equipment includes air conditioners and lighting, for air conditioners, there are energy-saving modes 1-10. Energy-saving mode 1 is in cooling mode with the temperature set to 26℃ and the fan speed set to 3. Energy-saving mode 2 is in cooling mode with the temperature set to 26.5℃ and the fan speed set to 2. Energy-saving mode 3 is in heating mode with the temperature set to 25℃ and the fan speed set to 1. Other energy-saving modes are not listed. For lighting, there are energy-saving modes 1-5. Energy-saving mode 1 includes turning on only the main light with a brightness set to 3. Energy-saving mode 2 includes turning on both the main light and the four corner incandescent bulbs with the main light's brightness set to 2. Other energy-saving modes are not listed. The standard carbon reduction strategy includes the selection strategy for the energy-saving mode. For example, there are standard carbon reduction strategies 1-3, corresponding to numerical ranges 1, 2, and 3, respectively. When selecting a standard carbon reduction strategy, first determine the difference between the first average value and the second threshold. If the difference is within numerical range 1, then standard carbon reduction strategy 1 is selected; if the difference is within numerical range 2, then standard carbon reduction strategy 2 is selected.

[0063] The larger the difference between the first average value and the first threshold, the greater the degree to which actual electricity consumption exceeds planned electricity consumption, and the more stable the standard carbon reduction strategy should be selected. This embodiment also calculates the modification probability for each energy-saving mode. For example, after adjusting the air conditioner to energy-saving mode 1, the modification probability is the probability that the user might manually change the adjusted energy-saving mode. In the initial state, a default modification probability is set for each energy-saving mode. For example, in cooling mode, the higher the temperature of the energy-saving mode, the higher its modification probability. Therefore, the greater the degree to which actual electricity consumption exceeds planned electricity consumption, the more important it is to select an energy-saving mode that will not be adjusted, thereby maximizing energy-saving performance.

[0064] Based on the above, Standard Carbon Reduction Strategy 1 aims to minimize the probability of modification when adjusting air conditioning and lighting. Standard Carbon Reduction Strategy 3 aims to maximize energy savings when adjusting air conditioning and lighting. For example, let's choose Standard Carbon Reduction Strategy 1 as an electricity carbon reduction measure. Before implementing the measure, we first obtain the electricity reduction amount for each independent area. The electricity reduction amount is how much electricity consumption needs to be reduced in an independent area on a given day or month; here, we use a day as the time span for example. If the electricity reduction amount for an independent area is 10 kWh, and if energy-saving mode 1 is used, calculations show a first combination. This first combination adjusts the air conditioning to energy-saving mode 1 and the lighting to energy-saving mode 2. Under energy-saving mode 1, the air conditioning can save 8 kWh of electricity on a given day, and under energy-saving mode 2, the lighting can save 1.5 kWh on a given day. The combination of these two is greater than the electricity reduction amount; therefore, energy-saving modes 1 and 2 are chosen as the first combination.

[0065] Analysis shows that when using the first combination 1, 5, and 7, the current reduction in electricity consumption is greater than or equal to the reduction in electricity consumption. In this case, the first combination 1, 5, and 7 are used as the second combination. In the second combination 1, 5, and 7, the modification probabilities of air conditioners are 50%, 60%, and 70%, respectively, and the modification probabilities of lighting are 55%, 62%, and 77%, respectively. Since standard carbon reduction strategy 1 is selected, the operating mode of the electrical equipment is adjusted according to the second combination 1.

[0066] In this embodiment, determining the electricity consumption reduction amount for each target area includes the following steps:

[0067] The planned power consumption of the construction area is broken down into daily restricted power consumption. Based on the historical power consumption sequence of each independent area, the restricted power consumption is further divided into regional power consumption. A switching time point is set every day. The actual power consumption sequence of the independent area before the switching time point is obtained by power sensors. The predicted power consumption sequence from the switching time point to the end of the day is predicted. Based on the predicted power consumption sequence and the actual power consumption sequence, the cumulative power consumption of each independent area is calculated. The difference between the cumulative power consumption and the regional power consumption is used as the power consumption reduction.

[0068] First, the estimated construction period and planned power consumption for the construction section are obtained. The planned power consumption is divided by the estimated construction period to obtain the daily restricted power consumption. To achieve a reasonable allocation of restricted power consumption, the restricted power consumption is divided into regional power consumption for each independent area based on the historical power consumption sequence of each independent area. Specifically, the average daily power consumption of each independent area is obtained through the historical power consumption sequence, and then allocated according to the ratio of the average daily power consumption of each independent area. For example, if the average power consumption of independent area 1 and independent area 2 is 1:2, and the restricted power consumption is 9kW, then the regional power consumption of independent area 1 is 3kW, and the regional power consumption of independent area 2 is 6kW.

[0069] The prediction time point is set to 16:00 every day. The actual electricity consumption of each independent area is obtained through power sensors from 00:00 to 16:00 every hour. The actual electricity consumption is converted into an actual electricity consumption sequence. At the same time, the predicted electricity consumption sequence after 16:00 on the same day is predicted. The cumulative electricity consumption is obtained by adding each value in the actual electricity consumption sequence and the predicted electricity consumption sequence. The difference between the cumulative electricity consumption and the regional electricity consumption is the electricity reduction amount.

[0070] In this embodiment, predicting the predicted electricity consumption sequence from the switching time point to the end of the day includes the following steps:

[0071] The system obtains multiple actual electricity consumption sequences of different time lengths before the switching time point as the first sequence. It then extracts a second sequence from the historical electricity consumption sequence that has the same time length as each of the first sequences. The system selects the second sequences with the highest similarity to each of the first sequences as the third sequence. Finally, it obtains a fourth sequence from the historical electricity consumption sequence that is after the third sequence and has the same length as the predicted electricity consumption sequence. The system then clusters the fourth sequence to obtain multiple clusters. The system selects the cluster that includes the most fourth sequences as the target cluster. Finally, it selects a fourth sequence from the target cluster as the predicted electricity consumption sequence.

[0072] The first sequence has time lengths of 4 hours, 6 hours, 8 hours...16 hours, with the switching time being 16:00 daily. Therefore, the portion from 12:00 to 16:00 in the actual electricity consumption sequence is selected as the 4-hour first sequence, and the portion from 10:00 to 16:00 is selected as the 6-hour first sequence. The remaining first sequences are generated in the same way. After this, portions of the corresponding time periods from the historical electricity consumption sequence are selected as the second sequence. The similarity between each second sequence and the corresponding time interval of the first sequence is calculated. Similarity can be measured using Euclidean distance, DTW algorithm, etc. Then, the four second sequences with the highest similarity to each first sequence are selected as the third sequence. In other embodiments, three or five second sequences can be selected. Then, the fourth sequence following each third sequence is obtained. For example, in the historical electricity consumption sequence, the second sequence between 12:00 and 16:00 on April 1 has a high similarity to the first sequence between 12:00 and 16:00 on the same day. Therefore, the second sequence is selected as the third sequence, and the sequence between 16:00 and 00:00 on April 1 is extracted as the fourth sequence.

[0073] The fourth sequences are clustered based on their similarity to each other, ensuring high similarity among sequences within the same cluster. For example, clustering should result in a similarity greater than 80% among sequences within the same cluster. K-means or DBSCAN algorithms can be used for clustering. After clustering, the cluster containing the most fourth sequences is selected as the target cluster. The more fourth sequences a cluster contains, the more likely the electricity consumption trend included in that cluster will appear after the predicted time point. When selecting the predicted electricity consumption sequence, either a fourth sequence can be randomly selected from the clusters, or a fourth sequence used as the cluster center can be chosen.

[0074] This embodiment generates energy carbon reduction measures, including the following steps:

[0075] Calculate the second difference between the second average value and the second threshold. Based on the second difference, construct a consumption reduction function and a cost increase function for replacing fuel-powered machinery with new energy machinery. Solve the consumption reduction function and the cost increase function to obtain energy carbon reduction measures. The energy carbon reduction measures include the replacement quantity of fuel-powered machinery with new energy machinery. Change the machinery based on the replacement quantity to implement the energy carbon reduction measures.

[0076] Specifically, firstly, the second difference between the second average and the second threshold, and the average number of various types of machinery and equipment used in the construction area are calculated. The energy savings and cost increases resulting from replacing current energy consumption with new energy sources for each type of machinery and equipment are determined. The number of each type of machinery and equipment replaced with new energy sources is used as the independent variable. Based on the second difference, the energy savings, the cost increases, and the independent variables, an energy function and a cost function are constructed. An intelligent algorithm is then used to solve the energy function and cost function to obtain energy-saving and carbon-reduction measures. The energy function is, for example,... The cost function is, for example, ,in, The second difference, The maximum replacement cost is set in advance. This represents the total number of types of mechanical equipment. For the first The savings figures for each type of machinery and equipment For the first The number of replacements for each type of mechanical equipment For the first The above function is merely an example; those skilled in the art can construct other function forms with similar functions, and the algorithm for solving the function is existing technology and will not be described here.

[0077] like Figure 2 As shown, the present invention also provides a carbon reduction performance evaluation system for railway construction processes. This system is used to implement the methods described above, and includes:

[0078] The planning module obtains a project list and determines the planned consumption amount for each consumption factor based on the project list. Consumption factors include electricity consumption and energy consumption.

[0079] The calculation module sets the unit emission factor for each consumption factor, divides the railway construction route into multiple construction sections, and calculates the planned emission of each construction section based on the planned consumption and the unit emission factor.

[0080] The accounting module sets up monitoring devices at the construction site of the construction section. After the construction section is completed, it obtains the actual consumption of each consumption factor based on the monitoring devices, and calculates the actual emission based on the actual consumption and the unit emission factor.

[0081] The generation module generates a first sequence based on the planned emissions of each construction zone after a first number of construction zones, and generates a second sequence based on the actual emissions. The first and second sequences are then analyzed to determine carbon reduction measures.

[0082] The comparison module obtains the actual emissions of the construction area after implementing carbon reduction measures and passing through a second number of construction sections, and compares them with the corresponding planned emissions to evaluate the effectiveness of the carbon reduction measures.

[0083] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

[0085] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating carbon reduction performance during railway construction, characterized in that, include: Obtain a project list, and determine the planned consumption of each consumption factor based on the project list, wherein the consumption factors include electricity consumption and energy consumption; Set a unit emission factor for each of the consumption factors, divide the railway construction route into multiple construction sections, and calculate the planned emission amount for each of the construction sections based on the planned consumption amount and the unit emission factor; A monitoring device is installed at the construction site of the construction section. After the construction section is completed, the actual consumption of each of the consumption factors is obtained based on the monitoring device, and the actual emission is calculated based on the actual consumption and the unit emission factor. After a first number of construction intervals, a first sequence is generated based on the planned emissions of each construction interval, and a second sequence is generated based on the actual emissions. The first sequence and the second sequence are analyzed to determine carbon reduction measures. After implementing carbon reduction measures and passing through a second number of the construction sections, the actual emissions of the construction sections after implementing carbon reduction measures are obtained and compared with the corresponding planned emissions to evaluate the effectiveness of the carbon reduction measures. The process of obtaining the actual consumption amount of each consumption factor based on the monitoring device includes the following steps: The monitoring device includes power sensors and monitoring cameras. The construction area within the construction zone is divided into multiple independent areas. Power sensors are installed in each independent area. The power sensors count the electricity consumption of each independent area and generate a historical electricity consumption sequence for each independent area based on the electricity consumption. After the construction in the construction zone is completed, the historical electricity consumption sequence is summarized to generate a total electricity consumption. The total electricity consumption is multiplied by the corresponding unit emission factor to obtain the actual emission amount of the electricity consumption. The surveillance camera is installed at the entrance of the construction area. The surveillance video of the construction area is recorded by the surveillance camera. The surveillance video is analyzed based on the image recognition algorithm to obtain the type of mechanical equipment entering the site each day, the corresponding number of equipment entering the site, and the dwell time of each piece of mechanical equipment. The unit energy consumption of each type of mechanical equipment is set. The total consumption is calculated based on the number of equipment entering the site, the dwell time, and the unit energy consumption. The total consumption is multiplied by the corresponding unit emission factor to obtain the actual emission of the energy consumption. The analysis of the first sequence and the second sequence to determine carbon reduction measures includes the following steps: Both the first sequence and the second sequence include an electricity emission sequence corresponding to the electricity consumption and an energy emission sequence corresponding to the energy consumption. A first difference sequence is generated based on the electricity emission sequence included in the first sequence and the energy emission sequence included in the second sequence, and a second difference sequence is generated based on the energy emission sequence included in the second sequence. A first average value of the first difference sequence and a second average value of the second difference sequence are calculated. A first threshold and a second threshold are set. If the first average value is greater than the first threshold, an electricity carbon reduction measure is generated. If the second average value is greater than the second threshold, an energy carbon reduction measure is generated. The carbon reduction measures for generating electricity include the following steps: Multiple standard carbon reduction measures are preset, and multiple energy-saving modes are set for each type of power equipment. The standard carbon reduction measures include the selection strategy of the energy-saving mode for each type of power equipment. Each standard carbon reduction measure has a corresponding numerical range. The difference between the first average value and the first threshold is calculated. Based on the numerical range in which the difference is located, the corresponding standard carbon reduction measure is selected as the power carbon reduction measure. The independent region that serves as the target for the power carbon reduction measure is determined and defined as the target region. The amount of electricity consumption reduction in each target region is determined. Based on the historical execution records of the standard carbon reduction measures, the probability of power equipment being manually changed after being adjusted to various energy-saving modes is calculated. The combination of various energy-saving modes of power equipment that meets the amount of electricity consumption reduction is selected as the first combination. The selection strategy includes maximizing energy saving value and minimizing modification probability. Based on the selection strategy, a combination is selected from the first combination as the second combination. The operating mode of the power equipment in the independent area is adjusted according to the second combination to implement power carbon reduction measures.

2. The method according to claim 1, characterized in that, Determining the electricity reduction amount for each of the target areas includes the following steps: The planned electricity consumption of the construction area is decomposed into daily restricted electricity consumption. Based on the historical electricity consumption sequence of each independent area, the restricted electricity consumption is further divided into regional electricity consumption. A switching time point is set daily. The actual electricity consumption sequence of each independent area before the switching time point is obtained by power sensors. The predicted electricity consumption sequence from the switching time point to the end of the day is predicted. Based on the predicted electricity consumption sequence and the actual electricity consumption sequence, the cumulative electricity consumption of each independent area is calculated. The difference between the cumulative electricity consumption and the regional electricity consumption is used as the electricity consumption reduction amount.

3. The method according to claim 2, characterized in that, Predicting the forecasted electricity consumption sequence from the switching time point to the end of the day includes the following steps: The process involves obtaining multiple actual electricity consumption sequences of different time lengths prior to the switching time point as a first sequence, extracting a second sequence from the historical electricity consumption sequence that has the same time length as each of the first sequences, selecting multiple second sequences with the highest similarity to each of the first sequences as a third sequence, obtaining a fourth sequence from the historical electricity consumption sequence that is after the third sequence and has the same length as the predicted electricity consumption sequence, clustering the fourth sequence to obtain multiple groups, selecting the group that includes the most fourth sequences as the target group, and selecting one of the fourth sequences from the target group as the predicted electricity consumption sequence.

4. The method according to claim 3, characterized in that, Energy generation and carbon reduction measures include the following steps: Calculate the second difference between the second average value and the second threshold. Based on the second difference, construct a consumption reduction function and a cost increase function for replacing fuel-powered machinery with new energy machinery. Solve the consumption reduction function and the cost increase function to obtain energy carbon reduction measures. The energy carbon reduction measures include the number of replacements of fuel-powered machinery with new energy machinery. Change the machinery based on the number of replacements to implement the energy carbon reduction measures.

5. A carbon reduction performance evaluation system for railway construction processes, used to implement the method described in any one of claims 1-4, characterized in that, The system includes: The planning module obtains a project list and determines the planned consumption amount for each consumption factor based on the project list. The consumption factors include electricity consumption and energy consumption. The calculation module sets the unit emission factor for each of the consumption factors, divides the railway construction route into multiple construction sections, and calculates the planned emission amount for each construction section based on the planned consumption amount and the unit emission factor; The accounting module sets up a monitoring device at the construction site of the construction section. After the construction section is completed, it obtains the actual consumption of each of the consumption factors based on the monitoring device, and calculates the actual emission based on the actual consumption and the unit emission factor. The generation module generates a first sequence based on the planned emissions of each construction interval after passing through a first number of construction intervals, generates a second sequence based on the actual emissions, and analyzes the first sequence and the second sequence to determine carbon reduction measures. The comparison module, after implementing carbon reduction measures and passing through a second number of the construction sections, obtains the actual emissions of the construction sections after implementing carbon reduction measures, and compares them with the corresponding planned emissions to evaluate the effectiveness of the carbon reduction measures.

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