System dynamics-based vehicle network interaction environment sustainability comprehensive index determination method and device in multi-energy scene, computer equipment, storage medium and computer program product

Abstract

The invention relates to a vehicle network interaction environment sustainability comprehensive index determination method and device based on system dynamics in a multi-energy scene, computer equipment, a storage medium and a computer program product. The method comprises the following steps: constructing a system dynamics model for a vehicle network interaction environment, and obtaining simulation conditions corresponding to different energy scenes; the vehicle-network interaction environment relates to interaction between a vehicle and a power grid; the proportions of clean energy corresponding to different energy structures are different; based on the simulation conditions corresponding to the different energy scenes, simulating the system dynamics model to obtain sustainable comprehensive index data corresponding to the vehicle network interaction environment in the different energy scenes; and generating a scheduling strategy for the electric vehicle based on the sustainable comprehensive index data corresponding to the vehicle network interaction environment in the different energy scenes. By adopting the method, the electric vehicles can be accurately dispatched.

Description

Technical Field

[0001] The present application relates to the field of distribution network technology, and in particular to a method, device, computer equipment, storage medium and computer program product for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics. Background Art

[0002] As a representative of clean energy transportation, electric vehicles are gradually becoming the mainstream choice for future urban transportation.

[0003] Currently, assessments of the environmental impact of electric vehicles often focus solely on carbon emissions during their use phase, ignoring carbon emissions and fossil energy consumption throughout their lifecycle, resulting in incomplete assessments. Furthermore, without comprehensive consideration of the interactions and dynamic changes in multiple factors, such as the scale of electric vehicle development and energy mix, it is difficult to fully assess the long-term impact of vehicle-grid interaction. Consequently, it is difficult to efficiently dispatch electric vehicles and effectively reduce their environmental impact.

[0004] Therefore, there is a problem in traditional technologies that electric vehicles cannot be dispatched accurately. Summary of the Invention

[0005] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for determining the comprehensive environmental sustainability index of vehicle-network interaction in multi-energy scenarios based on system dynamics, which can accurately dispatch electric vehicles in response to the above technical problems.

[0006] A method for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics, including:

[0007] Construct a system dynamics model for the vehicle-grid interaction environment and obtain simulation conditions corresponding to different energy scenarios; the vehicle-grid interaction environment involves the interaction between vehicles and the power grid; different energy scenarios correspond to different energy structures; and different energy structures correspond to different proportions of clean energy.

[0008] Based on the simulation conditions corresponding to different energy scenarios, the system dynamics model is simulated to obtain the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios;

[0009] Based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios, a scheduling strategy for electric vehicles is generated; the scheduling strategy is used to schedule electric vehicles to participate in the clean energy consumption process.

[0010] In an exemplary embodiment, based on the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios, a dispatch strategy for electric vehicles is generated, including:

[0011] Based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under any energy scenario, determine the impact of different clean energy consumption ratios on the sustainability of the vehicle-grid interaction environment under each energy scenario; the clean energy consumption ratio is the proportion of electric vehicles involved in clean energy consumption;

[0012] Based on the impact of different clean energy consumption ratios in various energy scenarios on the sustainability of the vehicle-grid interaction environment, a scheduling strategy for electric vehicles is generated.

[0013] In an exemplary embodiment, the vehicle-grid interaction environment also involves the interaction between electric vehicles and traditional vehicles. Constructing a system dynamics model for the vehicle-grid interaction environment includes:

[0014] Construct a model for the dynamic evolution of the conversion relationship between electric vehicles and traditional vehicles, a quantitative assessment model for the global warming potential of electric vehicles, and a model for determining the fossil energy consumption of electric vehicles;

[0015] A system dynamics model is constructed based on the conversion dynamics evolution relationship model, the global warming potential quantitative assessment model and the fossil energy consumption determination model.

[0016] In an exemplary embodiment, a quantitative assessment model for global warming potential of electric vehicles is constructed, including:

[0017] Obtain carbon emission data of electric vehicles at all stages of their life cycle;

[0018] Based on the carbon emission data of electric vehicles at all stages of their life cycle, a quantitative assessment model of global warming potential is constructed.

[0019] In an exemplary embodiment, building a model for determining fossil energy consumption for electric vehicles includes:

[0020] Obtain fossil energy consumption data for electric vehicles at all stages of their life cycle;

[0021] Based on the fossil energy consumption data of electric vehicles at all stages of their life cycle, a model for determining fossil energy consumption is constructed.

[0022] In an exemplary embodiment, the comprehensive sustainability indicator data corresponding to the vehicle-grid interactive environment under any energy scenario includes the global warming potential of electric vehicles and the fossil energy consumption of electric vehicles under the energy scenario.

[0023] A device for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in multi-energy scenarios based on system dynamics, comprising:

[0024] The construction module is used to build a system dynamics model for the vehicle-grid interaction environment and obtain simulation conditions corresponding to different energy scenarios. The vehicle-grid interaction environment involves the interaction between vehicles and the power grid. Different energy scenarios correspond to different energy structures. Different energy structures have different proportions of clean energy.

[0025] The simulation module is used to simulate the system dynamics model based on the simulation conditions corresponding to different energy scenarios to obtain the corresponding comprehensive sustainability indicator data of the vehicle-grid interaction environment under different energy scenarios;

[0026] The scheduling module is used to generate scheduling strategies for electric vehicles based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios; the scheduling strategies are used to schedule electric vehicles to participate in the clean energy consumption process.

[0027] A computer device includes a memory and a processor, wherein the memory stores a computer program and the processor implements the steps of the above method when executing the computer program.

[0028] A computer-readable storage medium stores a computer program, which implements the steps of the above method when executed by a processor.

[0029] A computer program product comprises a computer program, which implements the steps of the above method when executed by a processor.

[0030] The above-mentioned method, device, computer equipment, storage medium and computer program product for determining the comprehensive sustainability index of the vehicle-grid interaction environment under multiple energy scenarios based on system dynamics, by constructing a system dynamics model for the vehicle-grid interaction environment and obtaining simulation conditions corresponding to different energy scenarios; the vehicle-grid interaction environment involves the interaction between vehicles and the power grid; different energy scenarios correspond to different energy structures; different energy structures correspond to different proportions of clean energy; based on the simulation conditions corresponding to different energy scenarios, the system dynamics model is simulated to obtain comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios; based on the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios, a scheduling strategy for electric vehicles is generated; the scheduling strategy is used to schedule electric vehicles to participate in the clean energy consumption process; in this way, by constructing a system dynamics model of the comprehensive sustainability index of the vehicle-grid interaction environment under multiple energy scenarios, the interaction between vehicles and the power grid can be simulated, and the impact of different energy structures and different clean energy consumption strategies on the sustainability of the vehicle-grid interaction environment can be determined, which is conducive to determining an accurate electric vehicle scheduling strategy to accurately schedule electric vehicles and improve the vehicle-grid interaction environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 This is an application environment diagram of a method for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics in one embodiment;

[0033] Figure 2 A flowchart of a method for determining a comprehensive indicator of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics in one embodiment;

[0034] Figure 3 FIG1 is a schematic diagram of the scale evolution of electric vehicles in one embodiment;

[0035] Figure 4 is a schematic diagram corresponding to a quantitative assessment model of the global warming potential of electric vehicles in one embodiment;

[0036] Figure 5 A schematic diagram of a model for determining fossil energy consumption of an electric vehicle in one embodiment;

[0037] Figure 6 A schematic diagram of the development paths of three energy structures in one embodiment;

[0038] Figure 7 A schematic diagram of changes in the global warming potential of electric vehicles under three energy structures in one embodiment;

[0039] Figure 8 Schematic diagram of fossil energy consumption of electric vehicles under three energy structures in one embodiment;

[0040] Figure 9 Schematic diagram of GWP changes under different clean energy consumption ratios in one embodiment;

[0041] Figure 10 Schematic diagram of ADP(f) changes under different clean energy consumption ratios in one embodiment;

[0042] Figure 11 A flowchart of a method for determining a comprehensive indicator of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics in another embodiment;

[0043] Figure 12This is a structural block diagram of a device for determining a comprehensive indicator of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics in one embodiment;

[0044] Figure 13 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0046] Existing technologies for assessing the environmental impact of electric vehicles (EVs) largely focus solely on carbon emissions during their use phase, ignoring carbon emissions and fossil energy consumption throughout their lifecycle, resulting in incomplete assessments. Furthermore, there is a lack of systematic models that comprehensively consider the interactions and dynamic changes of multiple factors, such as the scale of EV development and energy mix. This makes it difficult to fully assess the long-term impact of EVs in a vehicle-grid interaction environment, and fails to fully consider strategies for EVs to participate in clean energy consumption and their impact on improving environmental indicators.

[0047] This invention aims to construct a system dynamics model for comprehensive measurement indicators of the environmental sustainability of vehicle-grid interaction under multiple energy scenarios, comprehensively and quantitatively evaluate the global warming potential (GWP) and fossil energy consumption (ADP(f)) of electric vehicles throughout their life cycle, deeply analyze the conversion dynamics relationship between electric vehicles and traditional vehicles and the factors affecting the development scale, and study the impact of different regional energy structures and different clean energy consumption strategies on the environmental sustainability of vehicle-grid interaction, providing a scientific basis for policy formulation and supervision. At the same time, it explores the improvement effect of different strategies for electric vehicles' participation in clean energy consumption on environmental indicators to support the formulation of reasonable policies.

[0048] The method for determining the comprehensive index of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated with server 104 or placed on a cloud or other network server. Server 104 constructs a system dynamics model for the vehicle-grid interaction environment and obtains simulation conditions corresponding to different energy scenarios. The vehicle-grid interaction environment involves the interaction between vehicles and the power grid. Different energy scenarios correspond to different energy structures, and different energy structures have different proportions of clean energy. Based on the simulation conditions corresponding to different energy scenarios, server 104 simulates the system dynamics model to obtain comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios. Based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios, server 104 generates a scheduling strategy for electric vehicles. The scheduling strategy is used to schedule electric vehicles to participate in the clean energy consumption process. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can include smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0049] In an exemplary embodiment, Figure 2 As shown in the figure, a method for determining the comprehensive index of environmental sustainability of vehicle-grid interaction under multi-energy scenarios based on system dynamics is provided. Figure 1 The server 104 in the example is used as an example to illustrate the process, including the following steps S202 to S206.

[0050] Step S202: construct a system dynamics model for the vehicle-grid interaction environment and obtain simulation conditions corresponding to different energy scenarios; the vehicle-grid interaction environment involves the interaction between the vehicle and the power grid; different energy scenarios correspond to different energy structures; and different energy structures correspond to different proportions of clean energy.

[0051] Among them, the vehicle-grid interaction environment involves the interaction between vehicles (especially electric vehicles) and the power grid. This interaction can include vehicles supplying power to the grid (V2G, Vehicle-to-Grid), the grid supplying power to vehicles, and information exchange and coordination between vehicles and the grid.

[0052] Among them, the system dynamics model refers to a model that can be used to analyze the conversion dynamics relationship and development scale influencing factors between electric vehicles and traditional vehicles, and to study the impact of different energy structures and clean energy consumption strategies on the sustainability of the vehicle-grid interaction environment.

[0053] Among them, different energy scenarios can refer to application scenarios with different energy proportions. The proportions of different types of energy such as wind energy, solar energy, and fossil fuels are different in different energy scenarios.

[0054] Among them, the simulation conditions corresponding to different energy scenarios may have the same parts or different parts. Among them, the same parts in the simulation conditions corresponding to different energy scenarios may refer to the initial clean energy proportion in different energy scenarios, and the different parts in the simulation conditions corresponding to different energy scenarios may refer to the final clean energy proportion in different energy scenarios.

[0055] Among them, vehicles in the vehicle-grid interactive environment can include electric vehicles and traditional vehicles.

[0056] Optionally, the server constructs a system dynamics model for the vehicle-grid interaction environment and obtains simulation conditions corresponding to different energy scenarios.

[0057] In step S204 , the system dynamics model is simulated based on simulation conditions corresponding to different energy scenarios to obtain comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios.

[0058] Among them, the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios can represent the sustainability impact of different energy structures on the vehicle-grid interaction environment.

[0059] Optionally, the server simulates the system dynamics model based on simulation conditions corresponding to different energy scenarios to obtain comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios.

[0060] Step S206 : Based on the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios, a scheduling strategy for electric vehicles is generated; the scheduling strategy is used to schedule electric vehicles to participate in the clean energy consumption process.

[0061] Among them, the scheduling strategy can be used to schedule electric vehicles to participate in the consumption process of clean energy, thereby reducing the adverse impact on the environment.

[0062] Optionally, the server generates a scheduling strategy for electric vehicles based on comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios.

[0063] In the above-mentioned method for determining the comprehensive sustainability index of the vehicle-grid interaction environment under multiple energy scenarios based on system dynamics, a system dynamics model for the vehicle-grid interaction environment is constructed, and simulation conditions corresponding to different energy scenarios are obtained; the vehicle-grid interaction environment involves the interaction between vehicles and the power grid; different energy scenarios correspond to different energy structures; the proportion of clean energy corresponding to different energy structures is different; based on the simulation conditions corresponding to different energy scenarios, the system dynamics model is simulated to obtain the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios; based on the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios, a scheduling strategy for electric vehicles is generated; the scheduling strategy is used to schedule electric vehicles to participate in the clean energy consumption process; in this way, by constructing a system dynamics model of the comprehensive sustainability index of the vehicle-grid interaction environment under multiple energy scenarios, the interaction between vehicles and the power grid can be simulated, and the impact of different energy structures and different clean energy consumption strategies on the sustainability of the vehicle-grid interaction environment can be determined, which is conducive to determining an accurate electric vehicle scheduling strategy to accurately schedule electric vehicles and improve the vehicle-grid interaction environment.

[0064] In an exemplary embodiment, a scheduling strategy for electric vehicles is generated based on the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under different energy scenarios, including: determining the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under any energy scenario based on the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under any energy scenario; the clean energy consumption ratio is the proportion of electric vehicles participating in clean energy consumption; and generating a scheduling strategy for electric vehicles based on the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under each energy scenario.

[0065] Among them, the sustainable impact of different clean energy consumption ratios on the vehicle-grid interaction environment can refer to the long-term impact on the vehicle-grid interaction environment when electric vehicles participate in the clean energy consumption process to varying degrees.

[0066] Among them, the proportion of clean energy consumption can refer to the proportion of electric vehicles participating in clean energy consumption.

[0067] Optionally, the server determines the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under any energy scenario based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under any energy scenario. The server then generates a scheduling strategy for electric vehicles based on the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under each energy scenario.

[0068] In this embodiment, based on the comprehensive sustainability index data corresponding to the vehicle-grid interaction environment under any energy scenario, the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under the energy scenario is determined; the clean energy consumption ratio is the proportion of electric vehicles participating in clean energy consumption; according to the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under each energy scenario, a scheduling strategy for electric vehicles is generated; in this way, the sustainability impact caused by different energy scenarios and different clean energy consumption ratios can be accurately determined, which is conducive to accurately providing a reference basis for the scheduling strategy of electric vehicles.

[0069] In an exemplary embodiment, the vehicle-grid interactive environment also involves the interaction between electric vehicles and traditional vehicles, and a system dynamics model for the vehicle-grid interactive environment is constructed, including: constructing a conversion dynamics evolution relationship model between electric vehicles and traditional vehicles, and constructing a global warming potential quantitative assessment model for electric vehicles, and constructing a fossil energy consumption determination model for electric vehicles; constructing a system dynamics model based on the conversion dynamics evolution relationship model, the global warming potential quantitative assessment model and the fossil energy consumption determination model.

[0070] Among them, the conversion dynamics evolution relationship model between electric vehicles and traditional vehicles can refer to a model used to simulate the dynamic changing relationship between electric vehicles and traditional vehicles under the influence of multiple factors such as society, economy and the level of development of electric vehicles.

[0071] The global warming potential quantitative assessment model may refer to a model for quantifying the carbon dioxide equivalent emissions of a vehicle.

[0072] The fossil energy consumption determination model may be a model for determining the fossil energy consumption of a vehicle.

[0073] Optionally, the server constructs a conversion dynamics evolution relationship model between electric vehicles and traditional vehicles, a global warming potential quantitative assessment model for electric vehicles, and a fossil energy consumption determination model for electric vehicles. The server then constructs a system dynamics model based on the conversion dynamics evolution relationship model, the global warming potential quantitative assessment model, and the fossil energy consumption determination model.

[0074] When determining the comprehensive sustainability indicators of the vehicle-grid interaction environment under multi-energy scenarios based on system dynamics, this application uses a model architecture that includes an electric vehicle development modeling module, an electric vehicle global warming potential calculation module, and an electric vehicle fossil energy consumption calculation module. In this embodiment, "constructing a conversion dynamics evolution relationship model between electric vehicles and traditional vehicles" corresponds to the electric vehicle development modeling module, "constructing a quantitative assessment model for the global warming potential of electric vehicles" corresponds to the electric vehicle global warming potential calculation module, and "constructing a model for determining fossil energy consumption for electric vehicles" corresponds to the electric vehicle fossil energy consumption calculation module.

[0075] In this embodiment, a system dynamics model is constructed by building a model for the dynamic evolution of the conversion between electric vehicles and conventional vehicles, a quantitative assessment model for the global warming potential of electric vehicles, and a model for determining the fossil energy consumption of electric vehicles. Based on the dynamic evolution of the conversion, the quantitative assessment model for the global warming potential, and the model for determining the fossil energy consumption of electric vehicles, an accurate system dynamics model can be constructed, which facilitates the exploration of the interactions and dynamic changes between multiple factors and effectively assesses the impact of sustainability.

[0076] In an exemplary embodiment, a quantitative global warming potential assessment model for electric vehicles is constructed, including: obtaining carbon emission data of electric vehicles at various stages throughout their life cycle; and constructing a quantitative global warming potential assessment model based on the carbon emission data of electric vehicles at various stages throughout their life cycle.

[0077] Among them, the various stages of the entire life cycle may include the raw material acquisition stage, manufacturing and assembly stage, operation and use stage, and scrapping and recycling stage of the vehicle's entire life cycle.

[0078] Among them, the carbon emission data of electric vehicles at various stages of their life cycle may include carbon emission data at the raw material acquisition stage, carbon emission data at the manufacturing and assembly stage, carbon emission data at the operation and use stage, and carbon emission data at the scrapping and recycling stage.

[0079] In practical applications, the carbon emission data of electric vehicles in the raw material acquisition stage can be based on the list of components and materials of electric vehicles (covering core components such as fuel cell stacks, lithium battery packs, hydrogen storage tanks, motors and electronic control units, body, chassis, etc.), combined with the carbon emission data of the production process of each component material, to calculate the GWP contribution of each component in the raw material acquisition stage; the carbon emission data in the manufacturing and assembly stage can be obtained by statistically analyzing the energy consumption of electricity, heat energy and other energy in the manufacturing process, matching the carbon emission conversion coefficient of the corresponding energy type, and calculating the greenhouse gas emission equivalent of this stage; the carbon emission data in the operation and use stage can be the carbon emission trajectory of energy production during vehicle charging determined by system tracking for different energy supply paths; the carbon emission data in the scrapping and recycling stage can be obtained by quantitatively evaluating the carbon emission impact of the terminal disposal link based on the energy demand model of the vehicle dismantling process.

[0080] Optionally, the server obtains carbon emission data of electric vehicles at various stages throughout their life cycle, and then constructs a global warming potential quantitative assessment model based on the carbon emission data of electric vehicles at various stages throughout their life cycle.

[0081] In this embodiment, by obtaining carbon emission data of electric vehicles at various stages of their life cycle; constructing a global warming potential quantitative assessment model based on the carbon emission data of electric vehicles at various stages of their life cycle, a model for accurately assessing the global warming potential of electric vehicles can be constructed, which is conducive to the subsequent accurate determination of the evolution characteristics of the global warming potential under different energy structures and different degrees of clean energy consumption by electric vehicles.

[0082] In an exemplary embodiment, a fossil energy consumption determination model for electric vehicles is constructed, including: obtaining fossil energy consumption data of electric vehicles at various stages throughout their life cycle; and constructing a fossil energy consumption determination model based on the fossil energy consumption data of electric vehicles at various stages throughout their life cycle.

[0083] Among them, the fossil energy consumption data of electric vehicles at various stages of their life cycle may include the fossil energy consumption data of electric vehicles in the raw material acquisition stage, the fossil energy consumption data of electric vehicles in the manufacturing and assembly stage, the fossil energy consumption data of electric vehicles in the operation and use stage, and the fossil energy consumption data of electric vehicles in the scrapping and recycling stage.

[0084] In practical applications, the fossil energy consumption data of electric vehicles in the raw material acquisition stage can be based on the list of components and materials of electric vehicles (core components such as fuel cell stacks, lithium battery packs, hydrogen storage tanks, motors and electronic control units, body and chassis), combined with the fossil energy input in the production process of each component material, to calculate the chemical energy consumption value of each component in the raw material acquisition stage; the fossil energy consumption data of the manufacturing and assembly stage can be calculated by quantifying the energy consumption of electricity, heat energy and other energy in the manufacturing and assembly links, combined with the fossil energy consumption factor of the corresponding energy type, to obtain the contribution value of chemical energy consumption in this stage; the fossil energy consumption data of the operation and use stage can be the fossil energy consumption generated in the electricity production link calculated according to the differences in the energy supply paths of the charging power of electric vehicles; the fossil energy consumption data of the scrapping and recycling stage can be the energy consumption of the dismantling, material recycling and other links after the vehicle is scrapped, combined with the fossil energy consumption factor of the corresponding energy type, to determine the chemical energy consumption value of this stage.

[0085] Optionally, the server obtains fossil energy consumption data of the electric vehicle at each stage of its life cycle, and constructs a fossil energy consumption determination model based on the fossil energy consumption data of the electric vehicle at each stage of its life cycle.

[0086] In this embodiment, by obtaining the fossil energy consumption data of electric vehicles at various stages of their life cycle; constructing a fossil energy consumption determination model based on the fossil energy consumption data of electric vehicles at various stages of their life cycle, a model for accurately evaluating the fossil energy consumption of electric vehicles can be constructed, which is conducive to the subsequent accurate evaluation of the impact of different energy structures on the dynamic changes in fossil energy consumption.

[0087] In an exemplary embodiment, the comprehensive sustainability indicator data corresponding to the vehicle-grid interactive environment under any energy scenario includes the global warming potential of electric vehicles and the fossil energy consumption of electric vehicles under the energy scenario.

[0088] In this embodiment, by using the global warming potential of electric vehicles and the fossil energy consumption of electric vehicles as comprehensive sustainability indicator data, it is helpful to accurately evaluate the sustainability impact of electric vehicles on the vehicle-grid interaction environment.

[0089] To facilitate understanding by those skilled in the art, the following exemplary method for generating an electric vehicle dispatching strategy is provided, which specifically includes the following steps:

[0090] Step 1: Construct a system dynamics model for the vehicle-grid interaction environment, which mainly involves the electric vehicle development modeling module, the electric vehicle global warming potential calculation module, and the electric vehicle fossil energy consumption calculation module.

[0091] (1) Developing modeling modules for electric vehicles, Figure 3 A schematic diagram of the scale evolution of electric vehicles is provided as an example.

[0092] In practical applications, the main factors affecting the scale of electric vehicles include the initial ownership , purchase volume and scrap volume ,in:

[0093] (1)

[0094] (2)

[0095] (3)

[0096] is the total demand for automobiles, The proportion of electric vehicle purchases, is the scrapping rate of electric vehicles in one month. and scrapping of electric vehicles Affected by multiple factors, they cover many aspects of the development process and show dynamic changes. Their calculation formulas are formulas (2) and (3) respectively.

[0097] The main factors affecting the scale of traditional cars include initial ownership , purchase volume and scrap volume ,in:

[0098] (4)

[0099] (5)

[0100] (6)

[0101] This is the scrapping rate of traditional cars in one month.

[0102] The proportion of electric vehicle purchases mentioned above Affected by the price of electric vehicles and the attractiveness of electric vehicle products The impact of The calculation method can be expressed as:

[0103] (7)

[0104] (8)

[0105] (9)

[0106] (10)

[0107] is the attraction factor, is the price factor, is the price of electric vehicles, is the price of a traditional car, Subsidies for the purchase of electric vehicles, To support the efforts, is the price correction coefficient, Subsidy coefficient for the purchase of electric vehicles.

[0108] The appeal of electric vehicles The calculation method can be expressed as:

[0109] (11)

[0110] (12) (13) (14)

[0111] For electric vehicle range, is the expected range of electric vehicles; Charging time for electric vehicles, Expected charging time for electric vehicles; is the number of charging piles, The target number of charging stations; , , They are the range factor, charging factor, and convenience factor. , , , They are the current average range of electric vehicles, the current average charging time of electric vehicles, the current number of charging piles, and the number of charging piles built each month; For technology maturity.

[0112] As the demand for cars is affected by multiple factors such as urban society, economy and population, the amount of scrapped electric vehicles , the amount of traditional car scrapped and new automobile demand The total demand for cars can be expressed as:

[0113] (15) (16) (17) (18)

[0114] The number of cars per capita, To achieve the per capita car ownership target, is the automobile demand factor, is the population, is the average monthly growth of urban GDP, is the constant of the impact rate of GDP and population on electric vehicles.

[0115] Average monthly GDP growth of the above cities and population The calculation method can be expressed as:

[0116] (19)

[0117] (20)

[0118] (twenty one)

[0119] (twenty two)

[0120] is the initial value of the city’s GDP, is the GDP growth rate, is the average monthly population growth, is the initial value of population, is the population growth rate.

[0121] (2) For electric vehicle global warming potential calculation module, Figure 4 A schematic diagram corresponding to a quantitative assessment model of the global warming potential of electric vehicles is provided as an example.

[0122] In practice, the quantitative assessment of Global Warming Potential (GWP) is based on the Life Cycle Assessment (LCA) framework and employs the CML2001 methodology. The calculation process includes the following core steps: systematically quantifying CO2-equivalent emissions throughout a vehicle's lifecycle, integrating carbon emission data from four key stages: raw material acquisition, manufacturing and assembly, operation and use, and end-of-life recycling, ultimately forming a comprehensive lifecycle GWP assessment system. Among them, the carbon emission data in the raw material acquisition stage can be based on the list of components and materials of electric vehicles (covering core components such as fuel cell stacks, lithium battery packs, hydrogen storage tanks, motors and electronic control units, bodies, chassis, etc.), combined with the carbon emission data of the production process of each component material, to calculate the GWP contribution of each component in the raw material acquisition stage; the carbon emission data in the manufacturing and assembly stage can be calculated by statistically analyzing the energy consumption of electricity, heat energy and other energy in the manufacturing process, matching the carbon emission conversion coefficient of the corresponding energy type, and calculating the greenhouse gas emission equivalent of this stage; the carbon emission data in the operation and use stage can be the carbon emission trajectory of energy production during vehicle charging determined by system tracking for different energy supply paths; the carbon emission data in the scrapping and recycling stage can be based on the energy demand model of the vehicle disassembly process, and quantitatively evaluating the carbon emission impact of the terminal disposal link. This application can construct a quantitative assessment model of the global warming potential (GWP) of electric vehicles based on the above four stages, such as Figure 2 As shown in the figure, the evolution of GWP under different energy structures and different degrees of clean energy consumption by electric vehicles is explored.

[0123] Global Warming Potential of Electric Vehicles The average monthly carbon emissions of electric vehicles over their entire life cycle and the GWP value of carbon dioxide OK, where:

[0124] (twenty three)

[0125] The average monthly carbon emissions equivalent of the above electric vehicles over their entire life cycle Average monthly carbon emissions equivalent consumed by electric vehicle raw material acquisition , the average monthly carbon emissions equivalent consumed during the manufacturing and assembly phase of electric vehicles , the average monthly carbon emissions equivalent consumed by electric vehicles during their operation and use phase and the average monthly carbon emissions equivalent consumed in the recycling phase of electric vehicles It consists of four steps and is calculated as follows:

[0126] (twenty four)

[0127] The monthly average carbon emissions equivalent consumed in the acquisition of raw materials for the above electric vehicles Carbon emissions equivalent consumed by the raw material acquisition stage of an electric vehicle and electric vehicle purchases Sure:

[0128] (25)

[0129] The monthly average carbon emissions equivalent consumed in the manufacturing and assembly stages of the above electric vehicles Carbon emissions equivalent consumed in the manufacturing and assembly phase of an electric vehicle and electric vehicle purchases Sure:

[0130] (26)

[0131] The average monthly carbon emissions equivalent consumed by the above electric vehicles during their operation and use phase Carbon emissions equivalent consumed by an electric vehicle during its original operation phase and electric vehicle ownership Sure:

[0132] (27)

[0133] (28)

[0134] (29)

[0135] (30)

[0136] is the average monthly charge of an electric car, is the proportion of coal-fired power generation, is the electricity-to-coal conversion factor, is the coal-to-carbon conversion factor, is the average monthly mileage, is the electricity consumption of electric vehicles per kilometer, is the proportion of clean energy power generation, It is the proportion of electric vehicles in clean energy consumption.

[0137] The average monthly carbon emissions equivalent consumed in the above electric vehicle scrapping and recycling stage Carbon emissions equivalent consumed by the recycling phase of an electric vehicle and scrapped electric vehicles calculate:

[0138] (31)

[0139] (3) For the calculation module of fossil energy consumption of electric vehicles, Figure 5 A schematic diagram of a model for determining the fossil energy consumption of electric vehicles is provided as an example, which is used to study the impact of different energy structures on the dynamic changes in fossil energy consumption.

[0140] In practical applications, the Life Cycle Assessment (LCA) of fossil energy consumption (ADP(f)) is calculated using the CML2001 methodology. Fossil energy consumption data for electric vehicles during the raw material acquisition phase can be calculated based on the bill of materials for each component (fuel cell stack, lithium battery pack, hydrogen storage tank, motor and electronic control unit, body, chassis, and other core components), combined with the fossil energy inputs in each component's material production process. Fossil energy consumption data for the manufacturing and assembly phase can be calculated by quantifying the energy consumption of electricity, heat, and other energy sources during the manufacturing and assembly phase, combined with fossil energy consumption factors for the corresponding energy types, to determine the contribution of chemical energy consumption during that phase. Fossil energy consumption data for the operational and use phase can be calculated based on the differences in the energy supply paths of the electric vehicle's charging capacity, based on the fossil energy consumption generated during electricity production. Fossil energy consumption data for the scrapping and recycling phase can be determined by factoring in the energy consumption of post-scrapping vehicle disassembly and material recovery, combined with fossil energy consumption factors for the corresponding energy types, to determine the chemical energy consumption during that phase.

[0141] Fossil energy consumption of electric vehicles Average monthly fossil energy consumption in the acquisition of raw materials for electric vehicles , Average monthly fossil energy consumption during the manufacturing and assembly phase of electric vehicles , the average monthly fossil energy consumption of electric vehicles during their operation and use phase , the average monthly fossil energy consumption during the recycling phase of electric vehicles It consists of four links, which are expressed as:

[0142] (32)

[0143] The average monthly fossil energy consumption in the above-mentioned electric vehicle raw material acquisition stage Average monthly fossil energy consumption for the raw material acquisition stage of an electric vehicle and electric vehicle purchases calculate:

[0144] (33)

[0145] Average monthly fossil energy consumption during the manufacturing and assembly phase of the above electric vehicles Average monthly fossil energy consumption during the manufacturing and assembly phase of an electric vehicle and electric vehicle purchases calculate:

[0146] (34)

[0147] Average monthly fossil energy consumption during the operation and use phase of the above electric vehicles Average monthly fossil energy consumption of an electric vehicle during its operation phase and electric vehicle ownership calculate:

[0148] (35)

[0149] (36)

[0150] Average monthly fossil energy consumption during the recycling phase of the above-mentioned electric vehicles The average monthly fossil energy consumption of an electric vehicle during its recycling phase and the number of electric vehicles scrapped calculate:

[0151] (37)

[0152] Step 2: Based on the constructed system dynamics model, a case analysis is conducted, which involves setting simulation parameters, formulating different energy structure development paths, setting the initial model parameters, and analyzing the simulation results.

[0153] (1) Regarding the setting of simulation parameters, this application selected all electric vehicles and traditional vehicles in Region A as the research objects. Through detailed research, a rich statistical data yearbook of Region A was obtained, which provided a solid data foundation for analysis. In actual application, when setting the simulation time, the time step was set to 1 month, the initial time was set to January 2025, and the end time was set to January 2035, for a total of 121 months.

[0154] (2) Regarding the formulation of different energy structure development paths, this application makes the following assumptions and simulation plans for the development of clean energy. First, the proportion of clean energy at the beginning of the simulation is set to remain unchanged. At the beginning of 2025, the proportion of clean energy is 30%. Three different clean energy development paths are planned. In 2035, the proportion of clean energy is 50%, 55%, and 60%. Each clean energy proportion follows a linear increasing trend. The optimization scheduling strategy for electric vehicles is given, assuming that the proportion of electric vehicles in clean energy consumption is 60%, 70%, and 80%, respectively.

[0155] (3) For the setting of the initial parameters of the model, please refer to Table 1 below.

[0156] Table 1

[0157] (4) Analysis of simulation results: The development paths of the three energy structures are as follows: Figure 6 According to the different proportions of clean energy in 2035, it can be divided into three scenarios: when the proportion reaches 60%, it is defined as a rapid development scenario of clean energy; when the proportion reaches 55%, it is defined as a moderate development scenario of clean energy; when the proportion reaches 50%, it is defined as a slightly slower development scenario of clean energy.

[0158] When electric vehicles account for 80% of clean energy consumption, the changes in the global warming potential of electric vehicles under the three energy structures are as follows: Figure 7 As shown in the figure, the fossil energy consumption of electric vehicles under the three energy structures is as follows Figure 8 As shown. Figure 7 and Figure 8 According to data from the rapid clean energy development scenario, the GWP and ADP(f) of electric vehicles in January 2035 are 1.04×1010 kg and 3.92×1011 MJ, respectively. In the slower clean energy development scenario, the GWP and ADP(f) over the same period are 1.19×1010 kg and 4.49×1011 MJ, respectively. Compared to the slower clean energy development scenario, the rapid clean energy development scenario reduces GWP and ADP(f) by 12.6% and 12.7%, respectively. This significant downward trend demonstrates that the rapid development of clean energy plays a significant role in promoting the sustainability of the vehicle-grid interaction environment.

[0159] Furthermore, in the context of rapid development of clean energy, by optimizing the dispatching strategy of electric vehicles and enabling them to participate in the consumption process of clean energy, their environmental impact can be significantly reduced. Specifically, the GWP changes under different clean energy consumption ratios are as follows: Figure 9 As shown in the figure, the changes of ADP(f) under different clean energy consumption ratios are as follows: Figure 10 As shown in the two figures, when EVs account for 60% of clean energy consumption, the GWP and ADP(f) in January 2035 are 1.27×1010 kg and 4.78×1011 MJ, respectively. When this proportion increases to 80%, the GWP and ADP(f) decrease by 18.1% and 17.9%, respectively, compared to the 60% proportion. This result fully demonstrates that optimizing EV scheduling strategies and enabling their active participation in clean energy consumption significantly promotes the sustainable development of the vehicle-grid interactive environment.

[0160] The system dynamics model construction method of this application innovatively constructs a system dynamics model for comprehensive measurement indicators of vehicle-grid interactive environmental sustainability under multi-energy scenarios, comprehensively integrating the interactions and dynamic changes of multiple factors such as the scale of electric vehicle development and energy structure, making up for the shortcomings of incomplete existing technology assessments and providing a scientific basis for policy formulation and supervision.

[0161] This application's electric vehicle development module constructs a model for the dynamic evolution of the conversion relationship between electric vehicles and traditional vehicles based on multiple factors, including social, economic, and electric vehicle development levels, and further explores the dynamic relationship between the two. It considers in detail the impact of factors such as initial ownership, purchase volume, and scrap volume on electric vehicle scale, as well as the influence of price factors and product attractiveness on electric vehicle purchase share. Product attractiveness is closely related to driving range, charging time, and the number of charging stations. Furthermore, vehicle demand is also influenced by a combination of factors, including a city's social, economic, and demographic factors.

[0162] The global warming potential (GWP) calculation module of this application is based on the life cycle assessment (LCA) framework and adopts the CML2001 methodology system to accurately quantify the GWP of electric vehicles from the four major links of raw material acquisition, manufacturing and assembly, operation and use, and scrapping and recycling. It not only takes into account the carbon emissions of the vehicle itself, but also systematically tracks the carbon emission trajectory of energy production during the vehicle charging process, as well as the energy demand model of the vehicle disassembly process, and comprehensively evaluates the carbon emission impact of electric vehicles throughout their life cycle.

[0163] The fossil energy consumption (ADP(f)) calculation module of this application also adopts the CML2001 methodology to calculate the ADP(f) of electric vehicles from four stages: raw material acquisition, manufacturing and assembly, operation and use, and scrapping and recycling. It considers in detail the energy consumption type and quantity in each stage, as well as the corresponding fossil energy consumption factors, and accurately evaluates the fossil energy consumption of electric vehicles throughout their life cycle.

[0164] This application studies the impact of different regional energy structures and clean energy consumption strategies on the sustainability of the vehicle-grid interaction environment, as well as the improvement effects of different strategies for electric vehicles’ participation in clean energy consumption on environmental indicators. This can provide a scientific basis for policy formulation and supervision, and help promote the rational development of the electric vehicle industry and the sustainability of the vehicle-grid interaction environment.

[0165] In another embodiment, Figure 11 As shown in the figure, a method for determining the comprehensive index of environmental sustainability of vehicle-grid interaction under multi-energy scenarios based on system dynamics is provided. Figure 1 Taking the server 104 in the example as an example, the following steps are included:

[0166] Step S1102: construct a system dynamics model for the vehicle-grid interaction environment and obtain simulation conditions corresponding to different energy scenarios; the vehicle-grid interaction environment involves the interaction between the vehicle and the power grid; different energy scenarios correspond to different energy structures; and different energy structures correspond to different proportions of clean energy.

[0167] Step S1104 : simulating the system dynamics model based on the simulation conditions corresponding to the different energy scenarios to obtain sustainability comprehensive indicator data corresponding to the vehicle-grid interaction environment under the different energy scenarios.

[0168] Step S1106, based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interactive environment under any energy scenario, determine the impact of different clean energy consumption ratios on the sustainability of the vehicle-grid interactive environment under the energy scenario; the clean energy consumption ratio is the proportion of electric vehicles participating in clean energy consumption.

[0169] Step S1108: generating a scheduling strategy for electric vehicles based on the impact of different clean energy consumption ratios on the sustainability of the vehicle-grid interaction environment under various energy scenarios; the scheduling strategy is used to schedule the electric vehicles to participate in the clean energy consumption process.

[0170] It should be noted that the specific limitations of the above steps can be found in the specific limitations of the method for determining the comprehensive environmental sustainability index of vehicle-grid interaction in a multi-energy scenario based on system dynamics.

[0171] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0172] Based on the same inventive concept, the embodiments of the present application also provide a device for determining a comprehensive indicator of environmental sustainability of a vehicle-grid interaction in a multi-energy scenario based on system dynamics, which is used to implement the aforementioned method for determining a comprehensive indicator of environmental sustainability of a vehicle-grid interaction in a multi-energy scenario based on system dynamics. The implementation solution provided by this device is similar to the implementation solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for determining a comprehensive indicator of environmental sustainability of a vehicle-grid interaction in a multi-energy scenario based on system dynamics provided below can be found in the above-mentioned limitations of the method for determining a comprehensive indicator of environmental sustainability of a vehicle-grid interaction in a multi-energy scenario based on system dynamics, and will not be repeated here.

[0173] In an exemplary embodiment, Figure 12 As shown, a device for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics is provided, comprising: a construction module 1202, a simulation module 1204, and a scheduling module 1206, wherein:

[0174] Construction module 1202 is used to construct a system dynamics model for the vehicle-grid interaction environment and obtain simulation conditions corresponding to different energy scenarios; the vehicle-grid interaction environment involves the interaction between vehicles and the power grid; different energy scenarios correspond to different energy structures; and different energy structures correspond to different proportions of clean energy.

[0175] A simulation module 1204 is configured to simulate the system dynamics model based on simulation conditions corresponding to different energy scenarios to obtain comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios;

[0176] The scheduling module 1206 is used to generate a scheduling strategy for electric vehicles based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under different energy scenarios; the scheduling strategy is used to schedule electric vehicles to participate in the clean energy consumption process.

[0177] In an exemplary embodiment, the scheduling module 1206 is specifically used to determine the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under any energy scenario based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under any energy scenario; the clean energy consumption ratio is the proportion of electric vehicles participating in clean energy consumption; and generate a scheduling strategy for electric vehicles based on the sustainability impact of different clean energy consumption ratios on the vehicle-grid interaction environment under each energy scenario.

[0178] In an exemplary embodiment, the vehicle-grid interactive environment also involves the interaction between electric vehicles and traditional vehicles. Construction module 1202 is specifically used to construct a conversion dynamics evolution relationship model between electric vehicles and traditional vehicles, as well as to construct a global warming potential quantitative assessment model for electric vehicles, and to construct a fossil energy consumption determination model for electric vehicles; based on the conversion dynamics evolution relationship model, the global warming potential quantitative assessment model and the fossil energy consumption determination model, a system dynamics model is constructed.

[0179] In an exemplary embodiment, the construction module 1202 is specifically used to obtain carbon emission data of electric vehicles at various stages throughout their life cycle; and to construct a global warming potential quantitative assessment model based on the carbon emission data of electric vehicles at various stages throughout their life cycle.

[0180] In an exemplary embodiment, the construction module 1202 is specifically used to obtain fossil energy consumption data of electric vehicles at various stages of their life cycle; and to construct a fossil energy consumption determination model based on the fossil energy consumption data of electric vehicles at various stages of their life cycle.

[0181] In an exemplary embodiment, the comprehensive sustainability indicator data corresponding to the vehicle-grid interactive environment under any energy scenario includes the global warming potential of electric vehicles and the fossil energy consumption of electric vehicles under the energy scenario.

[0182] Each module in the aforementioned system dynamics-based device for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in a multi-energy scenario can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in the form of software in a computer device's memory, allowing the processor to call and execute the corresponding operations of each module.

[0183] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 13As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data for determining the comprehensive environmental sustainability index of vehicle-network interaction under multi-energy scenarios based on system dynamics. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining the comprehensive environmental sustainability index of vehicle-network interaction under multi-energy scenarios based on system dynamics is implemented.

[0184] Those skilled in the art will understand that Figure 13 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0185] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program. When executed by the processor, the computer program causes the processor to perform the steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics. The steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics can be the steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics in each of the above embodiments.

[0186] In one embodiment, a computer-readable storage medium is provided, storing a computer program. When executed by a processor, the computer program causes the processor to perform the steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics. The steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics may be the steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics in each of the aforementioned embodiments.

[0187] In one embodiment, a computer program product is provided, including a computer program. When executed by a processor, the computer program causes the processor to perform the steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics. The steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics may be the steps of the method for determining a comprehensive indicator of environmental sustainability for vehicle-grid interaction in a multi-energy scenario based on system dynamics in each of the above embodiments.

[0188] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0189] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0190] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in a multi-energy scenario based on system dynamics, characterized by: The method comprises: Construct a system dynamics model for the vehicle-grid interaction environment and obtain simulation conditions corresponding to different energy scenarios; the vehicle-grid interaction environment involves the interaction between the vehicle and the power grid; different energy scenarios correspond to different energy structures; and different energy structures correspond to different proportions of clean energy. Simulating the system dynamics model based on simulation conditions corresponding to the different energy scenarios to obtain comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under the different energy scenarios; Based on the sustainability comprehensive indicator data corresponding to the vehicle-grid interaction environment under the different energy scenarios, a scheduling strategy for electric vehicles is generated; the scheduling strategy is used to schedule the electric vehicles to participate in the clean energy consumption process.

2. The method according to claim 1, characterized in that The generating of a dispatching strategy for electric vehicles based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under the different energy scenarios includes: Based on the comprehensive sustainability index data corresponding to the vehicle-grid interactive environment under any of the energy scenarios, determining the impact of different clean energy consumption ratios on the sustainability of the vehicle-grid interactive environment under the energy scenario; the clean energy consumption ratio is the proportion of clean energy consumption participated in by the electric vehicles; According to the impact of different clean energy consumption proportions under each energy scenario on the sustainability of the vehicle-grid interaction environment, a scheduling strategy for the electric vehicle is generated.

3. The method according to claim 1, characterized in that The vehicle-grid interactive environment also involves the interaction between electric vehicles and traditional vehicles. The construction of a system dynamics model for the vehicle-grid interactive environment includes: Constructing a conversion dynamics evolution relationship model between the electric vehicle and the conventional vehicle, constructing a global warming potential quantitative assessment model for the electric vehicle, and constructing a fossil energy consumption determination model for the electric vehicle; The system dynamics model is constructed based on the conversion dynamics evolution relationship model, the global warming potential quantitative assessment model and the fossil energy consumption determination model.

4. The method according to claim 3, characterized in that The constructing of a quantitative global warming potential assessment model for the electric vehicle includes: Obtaining carbon emission data of the electric vehicle at all stages of its life cycle; The global warming potential quantitative assessment model is constructed based on the carbon emission data of the electric vehicle at each stage of its life cycle.

5. The method according to claim 3, characterized in that The constructing of a fossil energy consumption determination model for the electric vehicle includes: Obtaining fossil energy consumption data of the electric vehicle at all stages of its life cycle; The fossil energy consumption determination model is constructed based on the fossil energy consumption data of the electric vehicle at each stage of its life cycle.

6. The method according to claim 1, wherein The comprehensive sustainability indicator data corresponding to the vehicle-grid interactive environment under any of the energy scenarios include the global warming potential of electric vehicles and the fossil energy consumption of electric vehicles under the energy scenario.

7. A device for determining comprehensive indicators of vehicle-grid interaction environmental sustainability in multi-energy scenarios based on system dynamics, characterized by: The device comprises: A construction module is used to construct a system dynamics model for a vehicle-grid interaction environment and obtain simulation conditions corresponding to different energy scenarios; the vehicle-grid interaction environment involves the interaction between vehicles and the power grid; different energy scenarios correspond to different energy structures; and different energy structures correspond to different proportions of clean energy. a simulation module, configured to simulate the system dynamics model based on simulation conditions corresponding to the different energy scenarios, so as to obtain comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under the different energy scenarios; The scheduling module is used to generate a scheduling strategy for electric vehicles based on the comprehensive sustainability indicator data corresponding to the vehicle-grid interaction environment under the different energy scenarios; the scheduling strategy is used to schedule the electric vehicles to participate in the clean energy consumption process.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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