Carbon emission metering method and system of high-speed railway traction power supply system based on dynamic carbon emission factors

Abstract

The invention relates to the technical field of carbon emission metering of a high-speed railway tractive power supply system, in particular to a carbon emission metering method and system of a high-speed railway tractive power supply system based on a dynamic carbon emission factor, and is particularly suitable for carbon emission metering of the tractive power supply system under the access condition of new energy such as wind, light and the like. The invention discloses a carbon emission metering method of a high-speed railway traction power supply system based on a dynamic carbon emission factor. The carbon emission metering method comprises a carbon metering accounting boundary and an indirect carbon emission metering method. A dynamic carbon emission factor-based carbon emission metering system for a traction power supply system of a high-speed railway is characterized by comprising a data acquisition module, a dynamic carbon emission factor calculation module, a carbon emission metering module and a sensitivity analysis module. According to the accounting method for the indirect carbon emission of the traction power supply system, the source of the carbon emission of the traction power supply system can be revealed, and a scientific and accurate theoretical basis is provided for carbon metering in the railway industry.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission measurement for high - speed railway traction power supply systems, and specifically provides a carbon emission measurement method and system for high - speed railway traction power supply systems based on dynamic carbon emission factors, which is particularly applicable to carbon emission measurement of traction power supply systems under the condition of new energy access such as wind and light energy. Background Art

[0002] With the increase in the operating mileage of high - speed railways, the issues of energy consumption and carbon emissions have attracted increasing attention. As the main energy - consuming department in the "four - electric" system of high - speed railways, the accurate measurement of carbon emissions from the traction power supply system is the basis for realizing the low - carbon development of high - speed railways. The existing carbon emission accounting methods in the railway industry are mainly based on the life - cycle theory and calculate using regional or national average power carbon emission factors, which cannot accurately reflect the carbon emission sources of the traction power supply system. Especially under the condition of new energy access, the existing methods cannot effectively analyze the impact of clean energy such as wind and light energy on carbon emissions.

[0003] In the prior art, scholars such as Xie Hansheng and Wang Yong proposed carbon emission accounting methods for railways based on the life - cycle theory. However, these methods did not specifically target the carbon emission accounting of railway transportation subsystems, and the power carbon emission factors used were static regional or national averages, which could not accurately reflect the carbon emission sources of the traction power supply system. In addition, there is a lack of systematic research on the impact of new energy access on the carbon emissions of traction power supply systems in the prior art. Summary of the Invention

[0004] The purpose of the present invention is to provide a carbon emission measurement method and system for high - speed railway traction power supply systems based on dynamic carbon emission factors, which can accurately calculate the carbon emissions of the traction power supply system, analyze the impact of new energy access such as wind and light energy on carbon emissions, and provide a scientific basis for the low - carbon transformation of high - speed railways.

[0005] To achieve the above - mentioned purpose, the following technical solutions are provided:

[0006] A carbon emission measurement method for high - speed railway traction power supply systems based on dynamic carbon emission factors, characterized by including the following steps:

[0007] Step 1: Carbon measurement accounting boundary; the carbon emissions of the traction power supply system mainly include the carbon emissions of the traction power supply and transformation system, the control system, and the catenary system; the carbon emissions of the traction power supply and transformation system mainly consist of indirect carbon emissions caused by equipment power consumption and carbon emissions generated from raw materials consumed in equipment maintenance; the carbon emissions of the control system are mainly carbon emissions caused by power consumption and raw material consumption; the carbon emissions of the catenary system are mainly carbon emissions generated from raw material consumption.

[0008] Step 2. Indirect carbon emission measurement method; the carbon emissions of the traction power supply system mainly adopt the indirect emission calculation method, which is calculated by statistically counting the electricity consumed by the traction power supply system and combining the carbon dioxide emissions borne by unit electricity. The specific steps are as follows:

[0009] Step (1). Dynamic carbon emission factor calculation: Based on the power flow calculation of the power system and the carbon flow theory, establish a dynamic active power flow distribution matrix, a generator injection distribution matrix, a node active power flux matrix, a load distribution matrix, and a generator carbon emission intensity matrix, and calculate the dynamic carbon emission factor of the power system;

[0010] Step (2). Traction power supply system carbon emission model: According to the dynamic carbon emission factor, establish a traction power supply system carbon emission measurement model, calculate the carbon emissions of the traction substation, and further sum to obtain the total carbon emissions of the traction power supply system;

[0011] Step (3). Sensitivity analysis: Analyze the influence of factors such as the traction load size, the carbon emission intensity of thermal power units, the installed capacity and location of wind and light access on the carbon emissions of the traction power supply system.

[0012] Preferably, in step (1) of step 2, due to the uncertainty and randomness of wind and light output, and the traction load also has fluctuations, the power flow distribution of the power system will also change with the changes in wind and light output and the traction load, resulting in fluctuations in the carbon emissions of the traction power supply system; therefore, first establish a dynamic active power flow distribution matrix as shown in formula (1), where P ijt represents the power magnitude between node i and node j at time t:

[0013]

[0014] Through power flow calculation, the injection power of the generator set can be determined. Further, define a k×n-order generator set injection distribution matrix P Gt , as shown in formula (2), to reflect the connection mode of all generator sets and the power system:

[0015]

[0016] To describe the connection relationship between the traction power supply load and the power system, define a k×n-order load distribution matrix P Lt =(P Lmjt ) m×n describes the active load quantity; in the calculation of carbon emissions, especially in the theoretical framework of node carbon potential, the carbon potential of a node is mainly affected by the power flow; define the node active power flux matrix P Nt as shown in formula (3); when there is regenerative braking energy feedback of EMUs in the traction power supply system, the node active power flux matrix P of the upper-layer power systemNt P in ijt is negative:

[0017]

[0018] Let P Zt = [P Bt P G T , P Nt matrix can be expressed as Equation (4):

[0019] P Nt = diag(ξ n+k P Zt ) (4)

[0020] where ξ n+k is an (n + k)-dimensional column vector with all elements equal to 1;

[0021] When calculating the carbon emission flow, considering that different generator sets have different carbon emission characteristics, a carbon emission intensity matrix E G is constructed to represent the carbon emission performance of each generator set, as shown in Equation (5):

[0022] E G = [e G1 e G2 … e Gk T (5)

[0023] Furthermore, the definition of the carbon emission factor e Nit of the power system can be expressed as:

[0024]

[0025] where e Nit represents the carbon emission factor when there is power flow into node i at time t; P Bst is the active power of branch s at time t; P Git is the active power generated by the generator set connected to node i at time t; e Git is the carbon emission intensity of the generator set at time t; ρ st is the carbon flow density of branch s at time t.

[0026] Preferably, in step (2) of step two, the traction substation in the traction power supply system is used as a three-phase load of the external power grid, and its electricity carbon intensity is equal to the node carbon potential of its connection point in the external power grid. By calculating the carbon flow index of the power system, the carbon flow rate R, the carbon potential e Nit , and the carbon flow density ρ st, these three indicators clarify the carbon emission distribution of the power system with a definite topological structure. Based on this, a carbon measurement model of the traction power supply system with a time dimension can be further constructed, specifically as follows:

[0027] Firstly, according to the carbon potential of the branch start node, the branch carbon current density ρ can be replaced st , and equation (6) is changed to the following matrix form:

[0028]

[0029] Among them, is an N-dimensional unit row vector;

[0030] According to the definition of the node active power flux matrix, it can be obtained that:

[0031]

[0032] From equations (7) and (8), it can be obtained that:

[0033]

[0034] Expanding equation (9) to the entire system dimension, it can be obtained that:

[0035]

[0036] By transforming and arranging equation (10), the node carbon potential matrix can be obtained as:

[0037]

[0038] The carbon current rate corresponding to the traction substation can be calculated from the node carbon potential matrix and the load distribution matrix; the calculation is as follows:

[0039] R Lt = P Lt E Nt (12)

[0040] Through the above carbon emission flow calculation model, the carbon current rate vector of the traction substation and the branch carbon current rate vector can be obtained. By integrating this vector in the time dimension, the carbon emissions of the traction substation can be deduced; and by summing the carbon emissions of each traction substation in the traction power supply system, the carbon emissions of the traction power supply system can be obtained; the formula is as follows:

[0041]

[0042] In the formula, C TPSS is the carbon emissions of the traction power supply system, and R Ltj is the carbon emissions of the j-th traction substation at time t; it can be seen that the carbon emissions of the traction power supply system are mainly related to the load distribution matrix P Ltj, Node active power flux matrix P Ntj , Active power flow distribution matrix P Btj , Generator set injection distribution matrix P Gtj , Generator set carbon emission intensity matrix E Gj related.

[0043] Preferably, in step (3) of step two, taking each load size, generator carbon emission intensity, wind and light access amount, and wind and light access position as uncertainty factors, use formula (15) to conduct a sensitivity analysis on the influencing factors related to the carbon emissions of the traction power supply system;

[0044]

[0045] In the formula, S k is the sensitivity coefficient of the kth influencing factor to the carbon emissions of the traction power supply system, ΔC TPSS is the change in carbon emissions of the traction power supply system, ΔF k is the change in the kth influencing factor, F k is the total amount of the kth influencing factor, C TPSS is the carbon emissions of the traction power supply system, S k means that the kth influencing factor changes in the same direction as the carbon emissions of the traction power supply system, S k the kth influencing factor changes in the opposite direction to the carbon emissions of the traction power supply system, |S k | The larger it is, the more sensitive the traction power supply system is to the kth influencing factor.

[0046] A carbon emission measurement system for a high-speed railway traction power supply system based on dynamic carbon emission factors, characterized in that the carbon emission measurement system includes a data acquisition module, a dynamic carbon emission factor calculation module, a carbon emission measurement module, and a sensitivity analysis module;

[0047] The data acquisition module is used to collect the load data of the traction power supply system, the output data of new energy sources such as wind and light, and the carbon emission intensity data of thermal power units; the dynamic carbon emission factor calculation module calculates the dynamic carbon emission factors of the power system based on power system power flow calculation and carbon flow theory; the carbon emission measurement module calculates the carbon emissions of the traction substation according to the dynamic carbon emission factors, and further sums them to obtain the total carbon emissions of the traction power supply system; the sensitivity analysis module is used to analyze the influence of factors such as traction load size, thermal power unit carbon emission intensity, wind and light access capacity and position on the carbon emissions of the traction power supply system.

[0048] The beneficial effects of the present invention are as follows:

[0049] 1. The present invention proposes a method for dividing the carbon emission boundary of the traction power supply system, which refines the traction power supply system into individual traction substations for analysis. And it clarifies the two major components of the carbon emissions of the traction substation: one is the indirect carbon emissions generated on the power grid power supply side due to the operation of internal equipment and load power consumption, which accounts for the dominant proportion and is the core component of the carbon emissions of the traction power supply system; the other is the direct carbon emissions caused by the consumption of raw materials during equipment maintenance. This division method provides an effective path for accurately identifying and quantifying the carbon emission sources of the traction power supply system.

[0050] 2. The present invention proposes a method for calculating the indirect carbon emissions of the traction power supply system. By taking the traction load as a load node of the power system for systematic analysis, a calculation model of the dynamic carbon emission factor is established by comprehensively considering the access location of the traction substation in the upper-layer power system, the carbon emission intensity of thermal power units in the upper-layer power system, the access capacity and location of new energy. Calculating the carbon emissions of the traction power supply system using the dynamic carbon emission factor can clarify the power source of the traction power supply system and help the low-carbon transformation of the traction power supply system.

[0051] 3. By analyzing the influencing factors of the carbon emissions of the traction power supply system, it is found that in the topological structure of the example of the present invention, when the carbon emission intensity of the thermal power unit increases by 78.66%, the corresponding carbon emissions of the traction power supply system increase by 77.55%. The centralized and decentralized access of wind power and photovoltaic has different impacts on the carbon emissions of the traction power supply system. When the centralized access is close to the load center, it can effectively reduce the transmission and distribution losses, and the emission reduction effect is significant at low and medium penetration rates. However, at high penetration rates, the emission reduction benefits are weakened due to the problems of wind and light curtailment and transmission bottlenecks. The decentralized access reduces the transmission losses through multi-node layout and has higher flexibility, especially the access effect near the load center is more significant. However, the problem of wind and light curtailment also exists at high penetration rates. Generally speaking, the centralized access is suitable for areas with concentrated loads, while the decentralized access helps to improve the system flexibility and energy utilization rate. It is necessary to comprehensively optimize the access strategy to achieve better emission reduction effects. Description of the Drawings

[0052] Figure 1 It is a schematic diagram of the carbon emission composition of the traction power supply system in the present invention;

[0053] Figure 2 It is the indirect carbon measurement process of the traction power supply system in the present invention;

[0054] Figure 3 It is the topology of the MATPOWER case 30 example including the traction load in Embodiment 3 of the present invention;

[0055] Figure 4 It is the load data of the traction substation in Embodiment 3 of the present invention;

[0056] Figure 5Carbon emission factor of the traction substation in Embodiment 3 of the present invention;

[0057] Figure 6 Carbon emission factor of the traction substation under different carbon emission intensities of the No. 1 node thermal power unit in Embodiment 3 of the present invention;

[0058] Figure 7 Carbon emission factor of the traction substation under different carbon emission intensities of the No. 27 node thermal power unit in Embodiment 3 of the present invention;

[0059] Figure 8 Change curve of the carbon emission of the traction substation in Embodiment 3 of the present invention;

[0060] Figure 9 Carbon flow rate of the traction substation in Embodiment 3 of the present invention;

[0061] Figure 10 Carbon emissions of the traction power supply system under different carbon emission intensities in Embodiment 3 of the present invention;

[0062] Figure 11 Change of carbon emissions of the traction substation with centralized photovoltaic access to Node 26 in Embodiment 3 of the present invention;

[0063] Figure 12 Change of carbon emissions of the traction substation with centralized photovoltaic access to special nodes in Embodiment 3 of the present invention;

[0064] Figure 13 Change of carbon emissions of the traction substation with centralized wind power access to Node 26 in Embodiment 3 of the present invention;

[0065] Figure 14 Change of carbon emissions of the traction substation with centralized wind power access to special nodes in Embodiment 3 of the present invention;

[0066] Figure 15 Change of carbon emissions of the traction substation during decentralized photovoltaic access in Embodiment 3 of the present invention;

[0067] Figure 16 Change of carbon emissions of the traction substation during decentralized wind power access in Embodiment 3 of the present invention;

[0068] Figure 17 Sensitivity analysis of the influencing factors of the carbon emissions of the traction substation in Embodiment 3 of the present invention. Detailed implementation manners

[0069] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0070] Basis for Measuring Indirect Carbon Emissions of Traction Power Supply System in Embodiment 1

[0071] 1.1 Carbon Measurement and Accounting Boundary

[0072] The calculation results of the carbon emissions throughout the life cycle of the traction power supply system in existing literature show that the total carbon emissions in the life cycle of the catenary are 88.19 ktCO2e, the direct carbon emissions are 13.14 ktCO2e, accounting for 14.89% of the life cycle, and the other indirect carbon emissions are 74.55 ktCO2e, accounting for approximately 84.53% of the life cycle; the total carbon emissions in the life cycle of the traction substation are 2.88 ktCO2e, among which the direct carbon emissions are 0.08 ktCO2e, only accounting for 3.05% of the life cycle, and the other indirect carbon emissions are 1.92 ktCO2e, accounting for 74.00% of the life cycle

[17] . It shows that the carbon emissions of the traction power supply system are mainly indirect carbon emissions, and the carbon emissions caused by the power consumption of the EMU operation should also be included in the carbon emission accounting boundary of the traction power supply system. Therefore, the present invention proposes a method for calculating the indirect carbon emissions of the traction power supply system based on dynamic carbon emission factors. On the premise of clarifying the power source of the traction power supply system, the carbon emissions of the traction power supply system are comprehensively calculated in combination with the traction load.

[0073] The carbon measurement and accounting boundary is the basis for calculating carbon emissions and is used to determine which carbon emissions should be included in the responsibility scope of a specific activity or entity. The carbon emissions of the traction power supply system refer to the carbon emissions generated by the consumption of electric energy during the operation of the traction power supply system. Therefore, the present invention proposes an idea of unified calculation of relevant power-consuming equipment and loads of the traction power supply system to calculate the carbon emissions of the traction power supply system.

[0074] Figure 1It is a schematic diagram of the carbon emission composition of the traction power supply system. The traction power supply system is divided into three parts: the traction power transformation and distribution system, the control system, and the catenary system for calculation. The carbon emissions of the traction power transformation and distribution system are mainly composed of two types: indirect carbon emissions caused by the power consumption of each device in the system and carbon emissions generated by the raw materials consumed to maintain the normal operation of the equipment; the carbon emissions of the catenary system are mainly the carbon emissions generated by raw material consumption; for the control system, its carbon emissions are mainly the carbon emissions caused by power consumption and raw material consumption. The coordinated work of these devices is a prerequisite for ensuring the normal operation of the traction power supply system. Accurately defining the accounting boundary of the carbon emissions of the traction power supply system is not only a key step in deeply understanding the carbon emission composition of the system but also the basis for constructing a carbon emission accounting system.

[0075] 1.2 Indirect Carbon Emission Measurement Method

[0076] Carbon emission measurement methods are mainly divided into direct emission measurement methods and indirect emission measurement methods. The direct emission measurement method calculates the carbon dioxide emissions from fossil fuel combustion using the CO2 emission estimation method, mainly based on macro data statistics and converted according to the primary energy consumption. The indirect emission measurement method calculates by statistically counting the electricity consumed by the statistical entity from the local power system and combining the carbon dioxide emissions borne by the unit electricity consumption. Since the main energy consumption type of the traction power supply system is electricity, the calculation of the carbon emissions of the traction power supply system mainly adopts the indirect emission calculation.

[0077] In order to accurately analyze the power input situation of each unit to the traction substation, it is necessary to use the idea of power flow calculation for analysis. The calculation of the dynamic carbon emission factor of the traction power supply system can be completed using the carbon flow theory. Scholars such as Zhou Tianrui pioneered a new perspective on the carbon emissions of the power system in their research, that is, regarding it as a virtual network flow attached to the power flow and used to quantify the carbon emissions required to maintain the power flow of any branch in the power system. This concept is simply referred to as "carbon emission flow" or "carbon flow" in the field of the power system. As the basic theoretical framework for analyzing the carbon emission structure of the power system, the carbon flow theory not only provides an effective means for analyzing the carbon footprint of the power system but also fits the characteristics of the traction power supply system. This theory can accurately track and calculate the carbon emissions generated by the traction power supply system due to power consumption using the concept of carbon emission flow, providing a solid theoretical support for evaluating the system's carbon emission level, optimizing energy allocation, and formulating emission reduction strategies.

[0078] Embodiment 2 Indirect Carbon Emission Measurement Model of Traction Power Supply System

[0079] Based on the foregoing analysis, the carbon emissions of the traction power supply system mainly stem from the indirect carbon emissions generated by power consumption on the power generation side (i.e., the power source side). Therefore, when calculating the carbon emissions of the traction power supply system, it is necessary to deeply analyze the composition of its power sources. Given that the traction power supply system is usually composed of multiple (e.g., six) traction substations, in order to ensure the accuracy and pertinence of the calculation, the traction power supply system is refined to a single traction substation, and each traction substation is regarded as a three-phase load unit in the power system for calculation. Using the real-time output data of new energy units, the active power flow distribution of the power system including photovoltaic and wind power at different time points is calculated, and a carbon measurement model for the traction power supply system is established based on the carbon flow theory.

[0080] 2.1 Calculation of dynamic carbon emission factors

[0081] Due to the uncertainty and randomness of the output of wind and light, and the fluctuation of the traction load, the power flow distribution of the power system will also change with the changes in the output of wind and light and the traction load, resulting in fluctuations in the carbon emissions of the traction power supply system. Therefore, a dynamic active power flow distribution matrix is first established as follows, where P ijt represents the power magnitude between node i and node j at time t:

[0082]

[0083] Through power flow calculation, the injection power of the generator set can be determined, and a k×n order generator set injection distribution matrix P Gt is further defined to reflect the connection mode of all generator sets to the power system:

[0084]

[0085] To describe the connection relationship between the traction power supply load and the power system, a k×n order load distribution matrix P Lt =(P Lmjt ) m×n describes the active load quantity. In the calculation of carbon emissions, especially in the theoretical framework of node carbon potential, the node carbon potential is mainly affected by the power flow. The node active power flux matrix P Nt is defined as follows. When there is regenerative braking energy feedback from multiple units in the traction power supply system, the P Nt in the node active power flux matrix P ijt of the upper-layer power system is negative.

[0086]

[0087] Let P Zt =[P Bt P G T , P​Nt The matrix can be expressed as:

[0088] P Nt = diag(ξ n+k P Zt ) (4)

[0089] where ξ n+k is an (n + k)-dimensional column vector with all elements equal to 1.

[0090] When calculating the carbon emission flow, considering that different generator sets have different carbon emission characteristics, a carbon emission intensity matrix E G of the generator sets is constructed to represent the carbon emission performance of each generator set:

[0091] E G = [e G1 e G2 … e Gk T (5)

[0092] Furthermore, the definition of the carbon emission factor e Nit of the power system can be expressed as:

[0093]

[0094] where e Nit represents the carbon emission factor when there is power flow into node i at time t; P Bst is the active power of branch s at time t; P Git is the active power generated by the generator set connected to node i at time t; e Git is the carbon emission intensity of the generator set at time t; ρ st is the carbon flow density of branch s at time t.

[0095] 2.2 Indirect Carbon Accounting Model of Traction Power Supply System

[0096] The proposal of the dynamic carbon emission factor lays the foundation for establishing the carbon emission model of the traction power supply system. In this section, an indirect carbon accounting model of the traction power supply system including the dynamic carbon emission factor is first established, and then the indirect carbon accounting process of the traction power supply system is proposed, and a sensitivity calculation model is established to analyze the influencing factors of the indirect carbon emission of the traction power supply system.

[0097] 2.2.1 Indirect Carbon Accounting Mathematical Model

[0098] As a three-phase load of the external power grid, the traction substation in the traction power supply system has the same electricity carbon intensity as the node carbon potential where it is connected to the external power grid. By calculating the carbon flow indicators of the power system, the carbon flow rate R, the carbon potential e Nit , and the carbon flow density ρ st ​, these three indicators clarify the carbon emission distribution of the power system with a definite topological structure. Based on this, a carbon measurement model of the traction power supply system considering the time dimension can be further constructed.

[0099] First, according to the carbon potential at the initial node of the branch, the carbon current density ρ of the branch can be replaced st , and Equation (6) is changed to the following matrix form:

[0100]

[0101] where is an N-dimensional unit row vector.

[0102] According to the definition of the node active power flux matrix, we can obtain:

[0103]

[0104] From Equations (7) and (8), we can get:

[0105]

[0106] Expanding Equation (9) to the entire system dimension, we can obtain:

[0107]

[0108] By transforming and arranging Equation (10), the node carbon potential matrix can be obtained as:

[0109]

[0110] The carbon current rate corresponding to the traction substation can be calculated from the node carbon potential matrix and the load distribution matrix. The calculation is as follows:

[0111] R Lt = P Lt E Nt (12)

[0112] Through the above carbon emission flow calculation model, the carbon current rate vector of the traction substation and the carbon current rate vector of the branch can be obtained. By integrating this vector in the time dimension, the carbon emissions of the traction substation can be deduced. By summing up the carbon emissions of each traction substation in the traction power supply system, the carbon emissions of the traction power supply system can be obtained. The formula is as follows:

[0113]

[0114] In the formula, C TPSS is the carbon emissions of the traction power supply system, and R Ltj is the carbon emissions of the jth traction substation at time t. It can be seen that the carbon emissions of the traction power supply system are mainly related to the load distribution matrix P Ltj , the node active power flux matrix PNtj , active power flow distribution matrix P Btj , generator set injection distribution matrix P Gtj , generator set carbon emission intensity matrix E Gj .

[0115] 2.2.2 Indirect carbon measurement process of the traction power supply system

[0116] Based on the above analysis, the indirect carbon measurement process of the traction power supply system is established as shown in Appendix Figure 2 .

[0117] 2.2.3 Sensitivity analysis of indirect carbon emissions of the traction power supply system

[0118] Taking the load size, generator carbon emission intensity, wind and light access amount, and wind and light access location as uncertain factors, the sensitivity analysis of the influencing factors related to the carbon emissions of the traction power supply system is carried out using formula (15).

[0119]

[0120] In the formula, S k is the sensitivity coefficient of the kth influencing factor to the carbon emissions of the traction power supply system, ΔC TPSS is the change in carbon emissions of the traction power supply system, ΔF k is the change in the kth influencing factor, F k is the total amount of the kth influencing factor, C TPSS is the carbon emissions of the traction power supply system. S k means that the kth influencing factor changes in the same direction as the carbon emissions of the traction power supply system; S k means that the kth influencing factor changes in the opposite direction to the carbon emissions of the traction power supply system; |S k | The larger it is, the more sensitive the traction power supply system is to the kth influencing factor.

[0121] Example three - numerical example analysis

[0122] 3.1 Related parameter settings

[0123] As can be seen from the previous analysis, the carbon emissions of the traction power supply system are mainly related to the network topology structure, traction load size, generator set carbon emission intensity, generator injection power, and the number of traction substations. Therefore, this invention uses the Case30 numerical example in MATPOWER for simulation analysis, replacing the original balanced load by connecting the load of a certain traction substation in the western region to node 26 through a 110 kV line and a transformer. The simulation topology diagram is as Figure 3 . And taking Figure 4The daily load curve of a traction substation in the western region shown is used as the original data for analysis and calculation. The output models of thermal power units, wind power and photovoltaic units, etc. can be found in the literature. According to the literature, the carbon emission intensity of each thermal power unit in the topological structure is set to 320 - 1500 (unit: gCO2·(kW·h) -1 ) for analysis and calculation.

[0124] 3.2 Analysis of the impact of the carbon emission intensity of thermal power units on the indirect carbon emissions of the traction power supply system

[0125] The node carbon potential of the 26th node, that is, the carbon emission factor of the traction substation, can be calculated using formulas (7) - (12). Figure 5 For the change of the carbon emission factor of the traction substation, the carbon emission factor of the traction substation is mainly related to the traction load itself. From 0:00 to 7:00, the carbon emission factor of the traction substation remains unchanged because there are no trains passing through the power supply range of the traction substation during this period, and only the relevant equipment in the traction substation consumes electricity. Since there are negative values in the traction load data of the calculation example of the present invention, that is, there is regenerative braking energy recovery of EMUs. When there is braking energy recovery in the traction substation, the carbon emission factor of the traction substation is negative.

[0126] The carbon emission intensity of the thermal power unit at node 1 is changed for calculation, and the results are as Figure 6 shown. When the carbon emission intensity of the generator set at node 27 is changed, the calculation results of the carbon emission factor of the traction substation are as Figure 7 shown. By comparing Figure 5 and Figure 6 it can be seen that the change of the carbon emission intensity at node 1 has almost no impact on the carbon emission factor of the traction substation. However, as the carbon emission intensity of the generator set at node 27 increases, the carbon emission factor of the traction substation also shows an increasing trend. This is because in this topological structure, the electric energy of the traction substation is mainly provided by the generator set at node 27. Therefore, the carbon emission intensity of the generator set at node 27 has a significant impact on the carbon emission factor of the traction substation.

[0127] The change of the carbon emissions of the traction substation in the time dimension can be calculated using formulas (13) - (17), as Figure 8 shown. The carbon emissions from 0 to 15:00 are much higher than those from 15 to 24:00, which is consistent with the load data of the traction substation, proving that the carbon emissions of the traction substation are directly related to the magnitude of the traction load.

[0128] Figure 9This is the calculation result of the carbon flow rate of the traction substation. The carbon flow rate is defined as the carbon flow passing through with the power flow per unit time. Since the load of the traction substation changes with time, the power flow in the power system also changes. Therefore, it can be inferred that the change trend of the carbon flow rate of the traction substation is consistent with the change trend of the traction substation load.

[0129] Taking a traction power supply system with 6 traction substations as an example, further use formula (19) to calculate the indirect carbon emissions of the traction power supply system in one day as Figure 10 shown. It can be seen that the indirect carbon emissions of the traction power supply system are between 77.87 - 346.77 t / day. Since the electric energy of the traction substation in this calculation example is mainly provided by the thermal power unit at node 27, and there is a linear correlation between the carbon emission intensity of this thermal power unit and the indirect carbon emissions of the traction substation.

[0130] 3.3 Analysis of the Impact of Concentrated Access of Wind and Photovoltaic on the Indirect Carbon Emissions of the Traction Power Supply System

[0131] After the access of wind and photovoltaic to the distribution network containing traction load, the power ratio of traditional thermal power in the distribution network is reduced, and the use of fossil fuels is reduced from the source, thus effectively reducing the carbon emissions of traction load. The selection of the access node of wind and photovoltaic has a direct impact on the transmission and distribution losses. The closer the access position is to the load center, the more significant the emission reduction benefit of the system carbon emissions. However, under high penetration conditions, problems such as wind curtailment and photovoltaic curtailment may limit the utilization of clean energy and weaken the carbon emission reduction effect. In order to analyze the impact of concentrated access of wind and photovoltaic on the indirect carbon emissions of the traction power supply system, in this section, photovoltaic and wind power are concentratedly accessed to the distribution network system, and the impact of the access capacity on the carbon emissions of the traction substation is analyzed.

[0132] 3.3.1 Concentrated Access of Photovoltaic

[0133] Figure 11 and Figure 12 show the changes in the carbon emissions of the traction substation when photovoltaic is concentratedly accessed to node 26 and special nodes of the distribution network system. It can be seen from the figure that when photovoltaic is concentratedly accessed to node 26, that is, the node where the traction substation is located, the carbon emissions of the traction substation decrease significantly. When the access ratio increases from 0 to 200%, the carbon emissions of the traction substation decrease by 57.23%. From Figure 12 it can be seen that with the change of the access node, the decline amplitude of the carbon emissions of the traction substation is different. When the penetration rate is low, the carbon emissions corresponding to each access node vary greatly because the output of the photovoltaic unit is limited, and the access node position has a more significant impact on the power distribution and the start-stop of traditional thermal power units. As the access capacity of photovoltaic increases, the photovoltaic power gradually replaces the power supply of traditional thermal power. However, under high penetration, the marginal improvement effect of the system unit characteristics on carbon emissions weakens, resulting in a slowdown in the decline rate of the carbon emissions of the traction substation.

[0134] 3.3.2 Wind power centralized connection

[0135] Figure 13 And Figure 14 Shows the change of carbon emissions of traction substations when wind power is centrally connected to 26 nodes and special nodes of the distribution network system. As can be seen from Figure 13 it, when the wind power access capacity is small, the carbon emissions of traction substations decrease significantly. However, as the access capacity increases (120%-200%), due to factors such as the overall load characteristics of the distribution network and the flexibility of power source scheduling, the rate of decrease in carbon emissions of traction substations slows down. When the wind power supply capacity exceeds the change range of load demand, its emission reduction contribution tends to saturate, and the standby thermal power units in the system may need to operate inefficiently or even start and stop frequently to balance the wind power fluctuations, resulting in a slowdown in the marginal rate of decrease in carbon emissions.

[0136] Figure 14 Shows the change of carbon emissions of traction substations when wind power is centrally connected to special nodes of the distribution network system. When the access ratio is relatively low (0%-80%), the change range of carbon emissions at each node is not large, and the carbon emissions of some nodes even increase slightly. This is because the initially connected wind power has limited power and is difficult to significantly replace traditional thermal power, and the system scheduling may be affected by volatility, resulting in a decrease in the efficiency of standby thermal power units. When the access ratio reaches a certain threshold (about 80%-120%), the carbon emissions begin to decrease significantly. This indicates that wind power can gradually replace the power supply load of traditional thermal power, and the effect of carbon emission reduction appears. When the access ratio further increases (exceeding 120%), the rate of decrease in carbon emissions gradually increases. This is because during high-load periods, the large-scale access of wind power can cover more traction load demands, directly reducing the thermal power supply and thus significantly reducing carbon emissions.

[0137] 3.4 Analysis of the impact of distributed wind and solar power access on the indirect carbon emissions of the traction power supply system

[0138] The distributed access methods of wind power and photovoltaic power can reduce the length of the transmission and distribution path, reduce the transmission and distribution losses, and at the same time improve the local consumption capacity of clean energy, further enhancing the emission reduction benefits of the system. However, due to the small scale and large number of access points of distributed wind and solar power sources, their volatility and uncertainty pose higher requirements for system scheduling and stability. If not fully coordinated, it may also limit the utilization efficiency of clean energy. To analyze the impact of distributed wind and solar power access on the indirect carbon emissions of the traction power supply system, this section connects distributed photovoltaic and wind power to the distribution network system and analyzes the impact of different access positions and capacities on the carbon emissions of traction substations.

[0139] 3.4.1 Distributed photovoltaic access

[0140] To analyze the impact of photovoltaic (PV) distributed connection on traction load, the nodes in the topology are classified into three types: nodes close to traction load, load center nodes, and weak nodes at the far end for analysis. Among them, the nodes close to traction load directly support the traction load and stabilize its dynamic characteristics; while the load center nodes can disperse the traction load pressure and optimize the load distribution of the whole network; the weak nodes at the far end can compensate the terminal voltage and reduce the fluctuation risk of terminal power supply. Three representative nodes from the three types of nodes are selected for distributed PV connection. At this time, the calculation results of the carbon emissions of the traction substation are as Figure 15 shown.

[0141] When connecting to nodes 25, 27, and 30, the carbon emissions decrease most significantly in the high connection ratio stage (100%-200%). This is because these nodes are close to the traction load center, and PV power generation can directly meet the traction load demand, while reducing the transmission and distribution losses and improving the utilization efficiency of PV. When connecting to nodes 3, 10, and 24, the carbon emissions show a trend of "first increasing and then decreasing", and start to decrease rapidly after the connection ratio reaches 150%. This is because these nodes are far from the load center. In the initial stage, PV power generation is mainly used to meet the low load demand around, and cannot effectively replace the thermal power supply of the traction load. Instead, it causes certain transmission losses due to power transmission. When the connection ratio is relatively high, PV power generation gradually covers the traction load demand, and the substitution benefit begins to appear. When connecting to nodes 28, 29, and 30, these nodes are far from the main load center, and most of the PV power is used to meet the demand in other regions, and cannot effectively replace the thermal power supply in the traction load. Therefore, the overall decrease in the carbon emissions of the traction substation is the smallest, and the decreasing trend is relatively gentle.

[0142] 3.4.2 Wind power distributed connection

[0143] By analogy with the PV distributed connection scheme, wind power is distributedly connected to the distribution network system, and the calculated carbon emissions of the traction substation are as Figure 15 shown. It can be seen from the figure that after wind power is distributedly connected to the traction power supply system, the change of its carbon emissions is significantly affected by the connection node position and connection ratio: in the low connection ratio stage (0%-50%), the effect of wind power replacing thermal power is limited, the volatility of wind power is large, the utilization rate is limited, and the transmission losses may offset part of the emission reduction effect, so the emission reduction amplitude is small; in the medium ratio stage (50%-100%), especially when connecting the node group close to the load center, the emission reduction benefit is significantly improved; while in the high ratio stage (100%-200%), due to the transmission losses and wind curtailment problems, the emission reduction effect of the node group far from the load center tends to be saturated or weakened.

[0144] Compared with PV distributed connection, wind power is more dependent on the connection node position and grid dispatching due to its volatility, while PV is more suitable for connecting close to the load center due to its stable power generation characteristics, but also faces the problem of PV curtailment under high penetration.

[0145] 3.5 Sensitivity Analysis of Each Influencing Factor

[0146] As can be seen from the previous analysis, the factors affecting the carbon emissions of traction substations are the size of traction load, the carbon emission intensity of generators, the access amount of wind and light, and the access location of wind and light. Representative results among the four influencing factors are extracted and used in formula (15) for sensitivity analysis. The results are as Figure 17 shown. Among them, the sensitivity coefficient of the carbon emission intensity of Unit 27 thermal power unit to the carbon emissions of traction power supply is 1.01, which has a greater influencing ability compared to the photovoltaic access capacity of -0.96 and the wind power access capacity of -0.54. The sensitivity coefficient of the access location of wind and light is 2.64, indicating that the closer the access location is to the traction substation, the greater the impact on its carbon emissions. And the sensitivity coefficient of the load size to carbon emissions is 1.56, indicating that the impact of traction load on the carbon emissions of traction substations cannot be ignored.

[0147] 3.6 Analysis of Emission Reduction Measures

[0148] 1) The size of the load in the traction power supply system determines the indirect carbon emissions of the traction power supply system. By implementing energy-saving transformation and upgrading measures for EMU trains, the energy consumption level per unit operating mileage of EMUs can be reduced, directly reducing the carbon emissions of the traction power supply system.

[0149] 2) When there is no access of wind and light in the distribution network system, the greater the carbon emission intensity of the thermal power unit supplying power to the traction substation, the greater the indirect carbon emissions of the traction power supply system. Clean transformation and technological upgrading of thermal power units can be implemented to reduce the carbon emission factor of the traction power supply system by reducing their own carbon emissions, thereby reducing the overall carbon emissions of the traction power supply system.

[0150] 3) When there is access of wind and light in the distribution network system, the access location and capacity of wind and light have an impact on the indirect carbon emissions of the traction power supply system. Decentralized access has a better carbon reduction effect than centralized access. However, it is necessary to reasonably plan the access location and capacity of wind and light, optimize the decentralized access strategy of wind and light, and combine energy storage technology and flexible dispatching to effectively improve the carbon emission reduction ability of the system.

[0151] Conclusion

[0152] The method proposed in the present invention has certain reference value in the formulation of carbon emission accounting standards in the railway industry, and can also lay a theoretical foundation for the implementation of carbon quota mechanisms and other emission reduction policies in China's railway industry. By deeply analyzing the key influencing factors of carbon emissions in the traction power supply system, it can provide a theoretical basis for railway bureaus and their subordinate stations and sections to promote the low-carbon transformation of the traction power supply system. Based on the empirical analysis and case verification of the present invention, the main conclusions are summarized as follows:

[0153] 1) A method for dividing the carbon emission boundary of the traction power supply system is proposed. The traction power supply system is refined into individual traction substations for analysis. And the two major components of the carbon emissions of the traction substation are clarified: one is the indirect carbon emissions generated on the power grid power supply side due to the operation of internal equipment and load power consumption, which accounts for the dominant proportion and is the core component of the carbon emissions of the traction power supply system; the other is the direct carbon emissions caused by the consumption of raw materials during equipment maintenance. This division method provides an effective path for accurately identifying and quantifying the carbon emission sources of the traction power supply system.

[0154] 2) A method for calculating the indirect carbon emissions of the traction power supply system is proposed. The traction load is regarded as a load node of the power system for systematic analysis. A calculation model of the dynamic carbon emission factor is established by comprehensively considering the access position of the traction substation in the upper-layer power system, the carbon emission intensity of thermal power units in the upper-layer power system, the access capacity and position of new energy. Calculating the carbon emissions of the traction power supply system using the dynamic carbon emission factor can clarify the power source of the traction power supply system and help the low-carbon transformation of the traction power supply system.

[0155] 3) By analyzing the influencing factors of the carbon emissions of the traction power supply system, it is found that in the topological structure of the calculation example of the present invention, when the carbon emission intensity of the thermal power unit increases by 78.66%, the corresponding carbon emissions of the traction power supply system increase by 77.55%. The centralized and decentralized access of wind power and photovoltaic power has different effects on the carbon emissions of the traction power supply system. When the centralized access is close to the load center, it can effectively reduce the transmission and distribution losses, and the emission reduction effect is significant at low and medium penetration rates. However, at high penetration rates, the emission reduction benefits are weakened due to the problems of curtailment of wind and light and transmission bottlenecks. The decentralized access reduces the transmission losses through multi-node layout and has high flexibility, especially the access effect near the load center is more significant. However, the problem of curtailment of wind and light also exists at high penetration rates. Generally speaking, the centralized access is suitable for areas with concentrated loads, while the decentralized access helps to improve the system flexibility and energy utilization rate. It is necessary to comprehensively optimize the access strategy to achieve better emission reduction effects.

[0156] In summary, the method for calculating the indirect carbon emissions of the traction power supply system proposed by the present invention can reveal the sources of carbon emissions of the traction power supply system, providing a scientific and accurate theoretical basis for carbon measurement in the railway industry; the analysis results of the influencing factors related to the carbon emissions of the traction power supply system are of great significance for promoting the green and low-carbon development of the railway industry.

[0157] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. A carbon emission measurement method for the traction power supply system of high-speed railways based on dynamic carbon emission factors, characterized in that, It includes the following steps: Step 1, Carbon accounting boundary: The carbon emissions of the traction power supply system mainly include the carbon emissions of the traction power supply and transformation system, the control system, and the catenary system. The carbon emissions of the traction power supply and transformation system mainly consist of indirect carbon emissions caused by equipment power consumption and carbon emissions generated by raw materials consumed in equipment maintenance. The carbon emissions of the control system are mainly carbon emissions caused by power consumption and raw material consumption. The carbon emissions of the catenary system are mainly carbon emissions generated by raw material consumption. Step 2, Indirect carbon emission measurement method: The carbon emissions of the traction power supply system mainly adopt the indirect emission calculation method. By statistically analyzing the electricity consumption of the traction power supply system and combining it with the carbon dioxide emissions borne by unit electricity, the calculation is carried out. The specific steps are as follows: Step (1), Dynamic carbon emission factor calculation: Based on the power system power flow calculation and carbon flow theory, establish a dynamic active power flow distribution matrix, a generator set injection distribution matrix, a load distribution matrix, a node active power flux matrix, and a generator set carbon emission intensity matrix, and calculate the dynamic carbon emission factor of the power system. Step (2), Traction power supply system carbon emission model: According to the dynamic carbon emission factor, establish a traction power supply system carbon emission measurement model, calculate the carbon emissions of the traction substation, and further sum to obtain the total carbon emissions of the traction power supply system. Step (3), Sensitivity analysis: Analyze the influence of factors such as the traction load size, thermal power unit carbon emission intensity, wind and solar access capacity and location on the carbon emissions of the traction power supply system.

2. The carbon emission measurement method for the traction power supply system of high-speed railways based on dynamic carbon emission factors according to claim 1, wherein In step (1) of step two, due to the uncertainty and randomness of wind and solar power generation, and the volatility of traction load, the power flow distribution of the power system will also change with the changes in wind and solar power generation and traction load, resulting in fluctuations in the carbon emissions of the traction power supply system. Therefore, a dynamic active power flow distribution matrix is first established, as shown in Equation (1), where P ijt represents the power magnitude between node i and node j at time t: Through power flow calculation, the injection power of the generator sets can be determined, and a k×n order generator set injection distribution matrix P is further defined Gt , as shown in Equation (2), which is used to reflect the connection mode of all generator sets and the power system: In order to describe the connection relationship between the traction power supply load and the power system, a k×n order load distribution matrix P is defined Lt =(P Lmjt ) m×n Describe the active load; in the calculation of carbon emissions, especially in the theoretical framework of node carbon potential, the carbon potential of the node is mainly affected by the flow; define the node active flux matrix P Nt As shown in formula (3), when there is regenerative braking energy feedback from the EMU in the traction power supply system, the node active flux matrix P of the upper power system is Nt P ijt is negative: Let P Zt = [P Bt P G T , and the P Nt matrix can be expressed as Equation (4):​ P Nt = diag(ξ n+k P Zt ) (4) Among them, ξ n+k is an (n + k)-dimensional column vector with all elements being 1; When calculating the carbon emission flow, considering that different generator sets have different carbon emission characteristics, a carbon emission intensity matrix E of the generator sets is constructed G to represent the carbon emission performance of each generator set, as shown in Equation (5): E G = [e G1 e G2 … e Gk T (5)​ The definition of the further power system carbon emission factor e Nit can be expressed as: Among them, e Nit represents the carbon emission factor of the power flow flowing into node i at time t; P Bst is the active power of branch s at time t; P Git is the active power generated by the generator set connected to node i at time t; e Git is the carbon emission intensity of the generator set at time t; ρ st is the carbon flow density of branch s at time t.

3. The carbon emission measurement method for the traction power supply system of high-speed railways based on dynamic carbon emission factors according to claim 2, wherein In step (2) of step two, the traction substation in the traction power supply system acts as a three-phase load of the external power grid, and its electricity consumption carbon intensity is equal to the node carbon potential at which it is connected to the external power grid. By calculating the carbon flow index of the power system, the carbon flow rate R, the carbon potential e Nit , and the carbon flow density ρ st can be obtained. These three indicators clarify the carbon emission distribution of the power system with a determined topological structure. Based on this, a carbon metering model of the traction power supply system with a time dimension can be further constructed, specifically as follows: First, according to the carbon potential at the starting node of the branch, the carbon flux density ρ of the branch can be replaced st , and Equation (6) is changed to the following matrix form: wherein, is an N-dimensional unit row vector; According to the definition of the node active power flux matrix, it can be obtained that: From equations (7) and (8), it can be obtained that: Expanding equation (9) to the entire system dimension, it can be obtained that: By transforming and arranging equation (10), the node carbon potential matrix can be obtained as: The carbon flow rate corresponding to the traction substation can be calculated from the node carbon potential matrix and the load distribution matrix; the calculation is as follows: R Lt = P Lt E Nt (12) Through the above carbon emission flow calculation model, the carbon flow rate vector of the traction substation and the branch carbon flow rate vector can be obtained. By integrating this vector in the time dimension, the carbon emissions of the traction substation can be deduced; and by summing the carbon emissions of each traction substation in the traction power supply system, the carbon emissions of the traction power supply system can be obtained; the formula is as follows: Where C TPSS is the carbon emission of the traction power supply system, and R Ltj is the carbon emission of the j-th traction substation at time t. It can be seen that the carbon emission of the traction power supply system is mainly related to the load distribution matrix P Ltj , the node active power flux matrix P Ntj , the active power flow distribution matrix P Btj , the generator injection distribution matrix P Gtj , and the generator carbon emission intensity matrix E Gj .

4. A carbon emission measurement method for a high - speed railway traction power supply system based on dynamic carbon emission factors according to claim 3, characterized in that, In step (3) of step 2, taking each load size, generator carbon emission intensity, wind and solar access amount, and wind and solar access location as uncertain factors, use formula (15) to conduct sensitivity analysis on the influencing factors related to the carbon emissions of the traction power supply system. Where S k is the sensitivity coefficient of the k-th influencing factor to the carbon emissions of the traction power supply system, ΔC TPSS is the change in carbon emissions of the traction power supply system, ΔF k is the change in the k-th influencing factor, F k is the total amount of the k-th influencing factor, C TPSS is the carbon emissions of the traction power supply system, S k means that the k-th influencing factor changes in the same direction as the carbon emissions of the traction power supply system, S k the k-th influencing factor changes in the opposite direction to the carbon emissions of the traction power supply system, |S k | The larger it is, the more sensitive the traction power supply system is to the k-th influencing factor.

5. A carbon emission measurement system for the traction power supply system of high-speed railways based on dynamic carbon emission factors, characterized in that, The carbon emission measurement system includes a data acquisition module, a dynamic carbon emission factor calculation module, a carbon emission measurement module, and a sensitivity analysis module. The data acquisition module is used to collect the load data of the traction power supply system, the output data of new energy sources such as wind and solar, and the carbon emission intensity data of thermal power units. The dynamic carbon emission factor calculation module calculates the dynamic carbon emission factor of the power system based on the power flow calculation of the power system and the carbon flow theory; the carbon emission measurement module calculates the carbon emissions of the traction substation according to the dynamic carbon emission factor, and further sums them up to obtain the total carbon emissions of the traction power supply system; the sensitivity analysis module is used to analyze the influence of factors such as the traction load size, the carbon emission intensity of thermal power units, the installed capacity and location of wind and solar power on the carbon emissions of the traction power supply system.

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