A carbon emission quantification method for a road network and power grid coupled network

Abstract

The application provides a carbon emission quantification method of a road network and power grid coupling network, realizes overall carbon emission quantification calculation of a coupling network formed by a city traffic road network and a distribution network, specifically includes direct carbon emission generated in a fuel vehicle driving process and upstream power generation carbon emission generated in electric vehicle charging, and respectively gives a direct carbon emission quantification method of a fuel vehicle under the influence of a road network and power grid coupling and an upstream carbon emission quantification method corresponding to electric vehicle charging power. The method of the application is verified, the carbon emission quantification method considering the influence of a road and power coupling effect is effective, and by comparing the coupling result with the result without considering the coupling, the difference between the two is found, which has reference value for the low-carbon development of city traffic and a power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon emissions, and in particular but not exclusively to a carbon emission quantification method for a road network and power grid coupled network. BACKGROUND

[0002] Under the existing 2030 carbon peak and 2050 carbon neutral "double carbon" development goals in China, traffic electrification has become an inevitable trend of social development. Electric vehicles have the advantage of energy saving and emission reduction, and their ownership is increasing under the promotion of policy and technology. Electric vehicles have both traffic and electricity characteristics, and their driving and charging behaviors will more closely link road networks and power grids, forming a road network and power grid coupled network. As the main interactive medium of the road-electricity coupled network, the operating state of the power grid will be reflected in the charging price through the marginal price, affecting the charging load and driving behavior of electric vehicles, and further affecting the road network. Conversely, the congestion of the road network can also change the charging behavior of electric vehicles and thus change the load of the power grid.

[0003] From the perspective of the entire road network and power grid coupled network, in addition to electric vehicles, the carbon emission benefits of fuel vehicles still occupy an important proportion in the entire coupled network, so it is necessary to comprehensively understand and grasp the overall carbon emissions of the urban road-electricity coupled network.

[0004] At present, most of the research on carbon emission quantification only considers the carbon emissions generated by fuel vehicles during driving, but in fact, the analysis of low-carbon indicators for the urban road-electricity coupled network should also focus on the upstream equivalent carbon emissions generated by electric vehicles through charging and even consider the influence of road-electricity coupling benefits on the quantification of carbon emissions.

[0005] Therefore, there is a need to provide a new method to solve at least part of the above problems. SUMMARY

[0006] In view of one or more problems in the prior art, the present application provides a carbon emission quantification method for a road network and power grid coupled network, which fully considers the road conditions of urban traffic and the charging price of the power grid, models and analyzes the driving of fuel vehicles and electric vehicles and the charging selection of electric vehicles, and quantitatively calculates the overall carbon emissions of the road network and power grid coupled network.

[0007] The technical solution for achieving the object of the present application is as follows:

[0008] A carbon emission quantification method for a road network and power grid coupled network, comprising:

[0009] Calculate the direct carbon emissions generated by fuel vehicles during driving:

[0010]

[0011] wherein, is the carbon emission of the fuel vehicle at node n and time period t, n is a node of the coupling network of the road network and the power grid, and t is a sampling time period, is a sampling interval duration, g is a fuel vehicle serial number, and G n is the number of fuel vehicles participating in statistics at node n, is the carbon emission intensity of the fuel vehicle g per unit time, is the driving speed of the fuel vehicle g at time period t;

[0012] The upstream carbon emission corresponding to the charging power of the electric vehicle is calculated as follows:

[0013]

[0014] wherein, is the upstream carbon emission of the electric vehicle at node n and time period t, e is an electric vehicle serial number, and E n is the number of electric vehicles participating in statistics at node n, is the carbon emission intensity of the thermal power plant per unit power generation, is the charging power of the electric vehicle e at time period t;

[0015] The total carbon emission is calculated according to the direct carbon emission generated in the driving process of the fuel vehicle and the upstream carbon emission corresponding to the charging power of the electric vehicle as follows:

[0016]

[0017] wherein, is the total carbon emission of node n at time period t.

[0018] Further, the carbon emission quantification method of the coupling network of the road network and the power grid optimizes the space-time distribution of the charging power of the electric vehicle to reduce the upstream carbon emission corresponding to the charging power of the electric vehicle under the premise of the same total charging demand, models the driving and charging selection of the electric vehicle with the minimum total travel cost of the electric vehicle as the optimization objective, the cost includes the time cost and the fee cost of charging, obtains the optimization objective function of the driving and charging selection of the electric vehicle, when the remaining electric quantity of the electric vehicle is greater than 10% of the total electric quantity, the electric vehicle performs driving and charging selection according to the optimization objective function, and when the remaining electric quantity of the electric vehicle is less than 10% of the total electric quantity, the electric vehicle immediately charges nearby.

[0019] Further, the optimization objective function of the driving and charging selection of the electric vehicle in the carbon emission quantification method of the coupling network of the road network and the power grid is as follows:

[0020]

[0021] In the formula: T drive is the total driving time of the electric vehicle, T charge is the total charging queue and service time of the electric vehicle, E charge is the charging price of each charging pile or charging station, is the conversion coefficient of charging price and charging time.

[0022] Further, the carbon emission quantification method of the road network and power grid coupled network of the present application, the conversion coefficient is limited to: the more the user values the charging price, the larger the corresponding conversion coefficient ; the more the user values the charging time cost, the smaller the corresponding conversion coefficient .

[0023] Further, the carbon emission quantification method of the road network and power grid coupled network of the present application, the calculation method of the total driving time T drive of the electric vehicle is:

[0024]

[0025]

[0026] In the formula: v ij,t is the average driving speed of the vehicle between roads R i -R j , which is closely related to road grade, time, road traffic volume and other factors; 、 、 is the regression parameter, is the correction coefficient, which changes with the road grade; v0 is the design speed of each grade road; C ij,t is the traffic flow between roads R i -R j at time t; C ij,0 is the capacity of road R i -R j ; k is the number of road network nodes passed during vehicle driving; D ij,d is the road distance from the (d-1)th node to the dth node on the way, t d-1 is the time when the electric vehicle drives to the d-1th node.

[0027] Further, the carbon emission quantification method of the road network and power grid coupled network of the present application, the residual power of the electric vehicle t at time t is:

[0028]

[0029] In the formula: SOCt-1 is the power at the last power detection time point; is the driving distance from the t-1 period to the t period; is the power consumption per kilometer of the electric vehicle; is the driving energy efficiency coefficient of the electric vehicle, which is used to represent the energy loss generated by starting and braking.

[0030] Compared with the prior art, the above technical scheme has the following technical effects:

[0031] 1. The carbon emission quantification method of the road network and power grid coupled network fully considers the influence of the coupling effect of the urban traffic road network and the power distribution network on the behavior of the fuel vehicle and the electric vehicle, and models the driving path and charging selection of the electric vehicle based on this, and optimizes the driving and charging selection of the electric vehicle.

[0032] 2. The carbon emission quantification method of the road network and power grid coupled network comprehensively considers the overall carbon emission of the road network and power grid coupled network, which includes not only the direct carbon emission in the driving process of the fuel vehicle, but also the upstream carbon emission caused by the charging power of the electric vehicle, and can comprehensively reflect the overall carbon emission of the urban traffic.

[0033] 3. The carbon emission quantification method of the road network and power grid coupled network can optimize the path and charging selection of the electric vehicle user, and can reduce the travel and charging cost of the user as much as possible while quantifying the overall network carbon emission. DETAILED DESCRIPTION

[0034] The accompanying drawings are included to provide a further understanding of the present application, and are incorporated in and constitute a part of this specification, illustrate embodiments of the present application, and are used to explain the present application, but do not constitute a limitation on the present application. In the drawings:

[0035] Figure 1 A simplified topological graph of the road network and power grid coupled network of a city in an embodiment of the present application is shown.

[0036] Figure 2 A charging power diagram of the electric vehicle considering the influence of the urban road and power coupling effect in an embodiment of the present application is shown.

[0037] Figure 3 A comparison diagram of the carbon emission quantification results of each node in the two cases of considering and not considering the road and power coupling effect is shown.

[0038] Figure 4 A flowchart of the carbon emission quantification method of the road network and power grid coupled network of the present application is shown. DETAILED DESCRIPTION

[0039] For a further understanding of the present application, preferred embodiments thereof will be described in conjunction with examples, it being understood, however, that this description is made only by way of further illustration and is not intended to limit the scope of the present application as defined in the appended claims.

[0040] The description of this part is only for typical embodiments, and the present application is not limited to the scope described in the embodiments. The combination of different embodiments, the mutual replacement of some technical features in different embodiments, and the mutual replacement of some technical features in the same or similar prior art means are also within the scope of the description and protection of the present application.

[0041] As shown in Figure 4 The present application proposes a carbon emission quantification method for a road network and power grid coupling network, comprising:

[0042] S1) calculating the direct carbon emission generated in the driving process of a fuel vehicle:

[0043]

[0044] Wherein, is the carbon emission of the fuel vehicle at node n and time period t, n is a node of the road network and power grid coupling network, and t is a sampling time period, is the sampling interval duration, g is the serial number of the fuel vehicle, and G n is the number of fuel vehicles participating in statistics at node n, is the carbon emission intensity of the fuel vehicle g per unit time, is the driving speed of the fuel vehicle g at time period t.

[0045] S2) calculating the upstream carbon emission corresponding to the charging power of an electric vehicle:

[0046]

[0047] Wherein, is the upstream carbon emission caused by the electric vehicle at node n and time period t, e is the serial number of the electric vehicle, and E n is the number of electric vehicles participating in statistics at node n, is the carbon emission intensity of a thermal power plant per unit of power generation, is the charging power of the electric vehicle e at time period t.

[0048] The upstream carbon emission corresponding to the charging power of the electric vehicle depends on the driving and charging behavior of the electric vehicle. Under the premise of the same total charging demand, the upstream carbon emission corresponding to the charging power of the electric vehicle can be effectively reduced by optimizing the space-time distribution of the charging power of the electric vehicle, thereby reducing the overall carbon emission of the network. In the power system with both thermal power and clean energy supply, it is generally believed that the carbon emission generated by clean energy such as wind power and photovoltaic power is less than that of thermal power, and the electricity price during the period when the wind power output is sufficient at night is lower than that during the day. The electric vehicle users will transfer the charging load to the night for the purpose of optimizing the charging cost, which can not only reduce their own charging cost, but also can absorb wind power and reduce the total carbon emission of the system. Therefore, the driving and charging selection of the electric vehicle is modeled by taking the minimum total travel cost of the electric vehicle as the optimization objective, which includes the time cost and the fee cost of charging, to obtain the optimization objective function of the driving and charging selection of the electric vehicle.

[0049] When the remaining electric quantity of the electric vehicle is greater than 10% of the total electric quantity, the electric vehicle performs driving and charging selection according to the optimization objective function. When the remaining electric quantity of the electric vehicle is less than 10% of the total electric quantity, the remaining electric quantity is insufficient to complete the subsequent driving plan, and at this time, the charging selection of the electric vehicle is no longer subject to the optimization objective of the optimization objective function, and the electric vehicle immediately charges nearby.

[0050] Electric vehicle t The remaining electric quantity at the moment is:

[0051]

[0052] In the formula, SOC t-1 is the electric quantity at the moment of the last electric quantity detection; is the driving distance from the t-1 period to the t period; is the electric consumption of the electric vehicle per kilometer; is the driving energy efficiency coefficient of the electric vehicle, which is used to represent the energy loss caused by starting and braking.

[0053] The optimization objective function of the driving and charging selection of the electric vehicle is:

[0054]

[0055] In the formula, T drive is the total driving time of the electric vehicle, T charge is the total charging queuing and service time of the electric vehicle, E charge is the charging price of each charging pile or charging station, is the conversion coefficient of the charging price and the charging time, and the conversion coefficient is limited to: the user who pays more attention to the charging price has a corresponding conversion coefficient The larger the value, the more users prioritize charging time costs, and the higher the corresponding conversion factor. The smaller.

[0056] Among them, the total travel time T drive The calculation method is as follows:

[0057]

[0058]

[0059] In the formula: v ij,t Let R be the road at time t. i -R j The average speed of cars in a given time is closely related to factors such as road grade, time, and traffic volume. , , For regression parameters, The correction factor varies with road grade; v0 is the design speed for each road grade; C ij,t Let R be the road at time t. i -R j Traffic flow between; C ij,0 For road R i -R j Traffic capacity; k is the number of road network nodes a vehicle passes through during its journey; D ij,d Let t be the road distance from the (d-1)th node to the dth node along the route. d-1 This represents the time it takes for the electric vehicle to travel to node d-1.

[0060] S3) Calculate the total carbon emissions based on the direct carbon emissions generated during the operation of gasoline vehicles and the upstream carbon emissions corresponding to the charging power of electric vehicles:

[0061]

[0062] in, Let be the total carbon emissions of node n during time period t.

[0063] Example 1

[0064] This embodiment selects the topology of the actual traffic road network and power grid of a certain city as the research object, which includes a total of 43 nodes. Among them, 6 public charging stations are arranged according to... Figure 1 The marked locations are nodes 8, 10, 11, 14, 19, 30, and 32, with several private charging piles installed at other nodes.

[0065] The carbon emission quantification method of this invention is used to predict the charging load of electric vehicles under the influence of urban road-electric coupling. The number of electric vehicles is set to 20,000. The spatiotemporal distribution characteristics of the charging results are as follows:Figure 2 As shown.

[0066] The carbon emission quantification method according to the present application quantitatively calculates the overall carbon emission of the road-electricity coupling network of the city, the sampling time interval is 1 hour, the number of fuel vehicles is set to 100000, the carbon emission intensity of fuel vehicles is 0.242 kg / km, and the upstream carbon emission intensity coefficient of electric vehicle charging is 0.650 kg / kWh.

[0067] Figure 3 The carbon emission quantification results considering the road-electricity coupling influence and not considering the road-electricity coupling influence are shown, and the values in the figure are the average values of the carbon emission of each node in each time period. Figure 3 It can be known that, since the city road-electricity coupling influence can change the charging selection of electric vehicles, the carbon emission distribution of each node is different from that directly calculated without considering the road-electricity coupling.

[0068] The description and application of the present application here are illustrative, and are not intended to limit the scope of the present application in the above embodiments. The effects or advantages related descriptions in the specification may not be embodied in actual experimental examples due to the uncertainty of specific condition parameters or other factors, and the effects or advantages related descriptions are not used to limit the scope of the present application. The variations and changes of the embodiments disclosed here are possible, and the alternatives and equivalent components of the embodiments are known to those skilled in the art. It should be clear to those skilled in the art that the present application can be realized in other forms, structures, arrangements, proportions, and with other components, materials and parts without departing from the spirit or essential characteristics of the present application. Other variations and changes of the embodiments disclosed here can be made without departing from the scope and spirit of the present application.

Claims

1. A method for quantifying carbon emissions from a road network and power grid coupled network, characterized in that, include: Calculate the direct carbon emissions generated during the operation of gasoline-powered vehicles: ； in, This represents the carbon emissions of gasoline-powered vehicles at node n and time period t, where n is the node in the road network and power grid coupling network, and t is the sampling time period. G represents the duration of the sampling interval, g represents the serial number of the fuel-powered vehicle, and G... n Let n be the number of fuel-powered vehicles included in the statistics. For fuel-powered vehicles, the carbon emission intensity per unit time is g. Let g be the speed of the fuel-powered vehicle during time period t; Calculate the upstream carbon emissions corresponding to the charging power of electric vehicles: ； in, E represents the upstream carbon emissions caused by electric vehicles at nodes n and t, where e is the electric vehicle number. n Let n be the number of electric vehicles included in the statistics. Carbon emission intensity per unit of electricity generated by a thermal power plant. The charging power of electric vehicle e during time period t; Under the premise of the same total charging demand, the upstream carbon emissions corresponding to the charging power of electric vehicles can be reduced by optimizing the spatiotemporal distribution of electric vehicle charging power. The driving and charging choices of electric vehicles are modeled with the goal of minimizing the total travel cost of electric vehicles. This cost includes time cost and charging fee cost. The optimization objective function for driving and charging choices of electric vehicles is as follows: ； In the formula: T drive T represents the total driving time of the electric vehicle. charge For electric vehicle charging queues and total service time, E charge The charging electricity price for each charging pile or charging station. This is the conversion factor between charging electricity price and charging time; when the remaining power of the electric vehicle is greater than 10% of the total power, the electric vehicle selects between driving and charging according to the optimization objective function; when the remaining power of the electric vehicle is less than 10% of the total power, the electric vehicle immediately charges at the nearest charging station. The overall carbon emissions are calculated based on the direct carbon emissions generated during the operation of gasoline-powered vehicles and the upstream carbon emissions corresponding to the charging power of electric vehicles: ； in, Let be the total carbon emissions of node n during time period t.

2. The method for quantifying carbon emissions from a road network and power grid coupling network according to claim 1, characterized in that, Conversion factor Limited to users who place greater emphasis on charging electricity prices, the corresponding discount factor is... The larger the value, the more users prioritize charging time costs, and the higher the corresponding conversion factor. The smaller.

3. The method for quantifying carbon emissions from a road network and power grid coupling network according to claim 1, characterized in that, Total driving time T of electric vehicles drive The calculation method is as follows: ； ； In the formula: v ij,t Let R be the road at time t. i -R j The average speed of cars in a given time is closely related to factors such as road grade, time, and traffic volume. , , For regression parameters, The correction factor varies with road grade; v0 is the design speed for each road grade; C ij,t Let R be the road at time t. i -R j Traffic flow between; C ij,0 For road R i -R j Traffic capacity; k is the number of road network nodes a vehicle passes through during its journey; D ij,d Let be the road distance from the (d-1)th node to the dth node along the route. This represents the time it takes for the electric vehicle to travel to node d-1.

4. The method for quantifying carbon emissions from a road network and power grid coupling network according to claim 1, characterized in that, The remaining battery power of the electric vehicle at time t for: ； Where: SOC t-1 The battery level at the time of the last battery level check; The distance traveled from time period t-1 to time period t; SOC refers to the energy consumption per kilometer of an electric vehicle. The driving efficiency coefficient of an electric vehicle is used to represent the energy loss during starting and braking.

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