V2g-based energy scheduling method, apparatus and device, storage medium, and product

Abstract

Disclosed in the present invention are a V2G-based energy scheduling method, apparatus and device, a storage medium, and a product. In a V2G energy scheduling scenario, an optimal carbon emission reduction objective function and a minimum cost objective function are constructed by considering factors such as a carbon emission amount of fuel consumed by a plug-in hybrid electric vehicle during return, a carbon emission amount of electric energy consumed during return, a carbon emission amount of fuel consumed when the plug-in hybrid electric vehicle performs energy scheduling with a power grid, a carbon emission amount generated when the electric energy is transmitted back to the power grid, the cost of the fuel consumed during return, and the cost consumed when the plug-in hybrid electric vehicle performs electric energy exchange with the power grid, and an optimal energy scheduling strategy is obtained by solving a multi-objective function, so as to control the plug-in hybrid electric vehicle to perform an energy scheduling operation on the basis of the fuel and / or the electric energy, thereby effectively reducing the carbon emission amount of energy scheduling in a V2G mode, facilitating environmental protection.

Description

V2G-based energy dispatching methods, devices, equipment, storage media, and products Technical Field

[0001] This invention relates to the field of vehicle technology, and more specifically, to a V2G-based energy dispatching method, apparatus, equipment, storage medium, and product. Background Technology

[0002] In recent years, with the increasing severity of global climate change and environmental pollution, and the growing demand for longer driving ranges, plug-in hybrid electric vehicles (PHEVs) have become a popular alternative to traditional gasoline-powered vehicles due to their combination of low carbon emissions and long driving range. Data from the China Automotive Technology and Research Center (CATARC) shows that PHEV sales growth rates over the past three years were 147%, 134%, and 85%, respectively. With the increasing popularity of PHEVs and the rapid development of vehicle-to-grid (V2G) technology, PHEVs will become an important flexible energy storage resource for the power grid.

[0003] Currently, in the Vehicle-to-Grid (V2G) mode, the energy dispatching of vehicles to the grid is generally optimized only with economic efficiency as the goal, lacking low-carbon optimization of energy dispatching, which is not conducive to environmental protection. Therefore, it is necessary to consider low carbon emissions to realize the energy dispatching of vehicles in the V2G mode. Summary of the Invention

[0004] Based on this, the present invention provides a V2G-based energy scheduling method, apparatus, device, storage medium and product to solve the defect of insufficient low-carbon optimization caused by the prior art which only considers economic factors in the energy scheduling of vehicles in the V2G mode.

[0005] To achieve the above objectives, embodiments of the present invention provide a V2G-based energy scheduling method, comprising:

[0006] Construct the optimal carbon reduction objective function and the minimum cost objective function:

[0007] in, It is the total carbon emissions of plug-in hybrid electric vehicles in the V2G energy dispatch scenario; It is the carbon emissions from the fuel consumed during the return trip; It is the carbon emissions from the electricity consumed during the return trip; E MF E represents the carbon emissions from the fuel consumed by the plug-in hybrid electric vehicle during time period t. BThe carbon emissions generated by the plug-in hybrid electric vehicle participating in V2G and sending electrical energy back to the grid during time period t; t is time period t, and T is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatch between the charging station and the grid. This refers to the total cost of the plug-in hybrid electric vehicle under the V2G energy dispatch scenario. C is the cost of the fuel consumed during the return trip. MF C is the cost of the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The cost incurred by the plug-in hybrid electric vehicle during time period t when exchanging electrical energy with the power grid through the charging station; the return trip is the process by which the plug-in hybrid electric vehicle returns to the owner's residence from the charging station after completing V2G.

[0008] Solving for the optimal carbon emission reduction objective function and the minimum cost objective function yields the optimal energy scheduling strategy;

[0009] The plug-in hybrid electric vehicle is controlled to perform energy dispatching operations according to the optimal energy dispatching strategy; wherein the energy dispatching operations include at least the plug-in hybrid electric vehicle using the fuel and / or the electrical energy to supply power to the power grid.

[0010] To achieve the above objectives, embodiments of the present invention also provide a V2G-based energy dispatching device, comprising:

[0011] The function building module is used to construct the optimal carbon reduction objective function and the minimum cost objective function:

[0012] in, It is the total carbon emissions of plug-in hybrid electric vehicles in the V2G energy dispatch scenario; It is the carbon emissions from the fuel consumed during the return trip; It is the carbon emissions from the electricity consumed during the return trip; E MF E represents the carbon emissions from the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The carbon emissions generated by the plug-in hybrid electric vehicle participating in V2G and sending electrical energy back to the grid during time period t; t is time period t, and T is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatch between the charging station and the grid. This refers to the total cost of the plug-in hybrid electric vehicle under the V2G energy dispatch scenario. C is the cost of the fuel consumed during the return trip. MF C is the cost of the fuel consumed by the plug-in hybrid electric vehicle during time period t. BThe cost incurred by the plug-in hybrid electric vehicle during time period t when exchanging electrical energy with the power grid through the charging station; the return trip is the process by which the plug-in hybrid electric vehicle returns to the owner's residence from the charging station after completing V2G.

[0013] The solution module is used to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain the optimal energy scheduling strategy;

[0014] An energy dispatch module is used to control the plug-in hybrid electric vehicle to perform energy dispatch operations according to the optimal energy dispatch strategy; wherein the energy dispatch operation includes at least the plug-in hybrid electric vehicle using the fuel and / or the electrical energy to supply power to the power grid.

[0015] To achieve the above objectives, embodiments of the present invention also provide a V2G-based energy scheduling device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the V2G-based energy scheduling method as described in any of the above embodiments.

[0016] To achieve the above objectives, embodiments of the present invention also provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the V2G-based energy scheduling method as described in any of the above embodiments.

[0017] To achieve the above objectives, embodiments of the present invention also provide a computer program product, including a computer program / instructions, which, when executed by a processor, implement the V2G-based energy scheduling method as described in any of the above embodiments.

[0018] Compared with existing technologies, the energy dispatching method, apparatus, device, storage medium, and product based on V2G disclosed in this invention firstly, in the V2G energy dispatching scenario, by considering factors such as the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle during the return trip, the carbon emissions of electricity consumed during the return trip, the carbon emissions of fuel consumed when the plug-in hybrid electric vehicle performs energy dispatching with the grid, the carbon emissions generated by sending electricity back to the grid during energy dispatching with the grid, the cost of the fuel consumed during the return trip, and the cost incurred when the plug-in hybrid electric vehicle exchanges electricity with the grid, an optimal carbon emission reduction objective function and a minimum cost objective function are constructed. Then, by solving the multi-objective functions, an optimal energy dispatching strategy is obtained. Finally, by controlling the plug-in hybrid electric vehicle to perform energy dispatching operations based on the vehicle's fuel and / or electricity according to the obtained optimal energy dispatching strategy, the carbon emissions of energy dispatching between the plug-in hybrid electric vehicle and the grid in V2G mode are effectively reduced, which is beneficial to environmental protection. Attached Figure Description

[0019] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 is a flowchart illustrating a V2G-based energy scheduling method according to an embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of a V2G-based energy dispatching device according to an embodiment of the present invention;

[0022] Figure 3 is a schematic diagram of the structure of a V2G-based energy dispatching device provided in an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] An embodiment of the present invention provides a V2G-based energy scheduling method, as shown in Figure 1, which is a flowchart illustrating the V2G-based energy scheduling method. Specifically, the V2G-based energy scheduling method includes steps S1 to S3:

[0025] S1. Construct the optimal carbon emission reduction objective function and the minimum cost objective function.

[0026] The optimal carbon emission reduction objective function and the minimum cost objective function are as follows:

[0027] in, This refers to the total carbon emissions of plug-in hybrid electric vehicles in a V2G energy dispatch scenario, where the subscript Q... B Q is the absolute value of the amount of electricity exchanged between a plug-in hybrid electric vehicle and the power grid during time period t, with the subscript Q. MF This represents the amount of fuel consumed during time period t. The subscript α indicates the vehicle mode, which includes vehicle charging mode (G2V), power supply mode (electricity V2G), and fuel supply mode (fuel V2G). Vehicle charging mode refers to the grid charging the plug-in hybrid electric vehicle (PHEV). Power supply mode refers to the use of electricity from the PHEV to supply power to the grid. Fuel supply mode refers to the use of fuel from the PHEV to supply power to the grid. Subscript a represents the proportion of fuel consumed for the return trip at the last moment relative to the remaining fuel. Subscript b represents the proportion of electricity consumed for the return trip at the last moment relative to the remaining electricity. Remaining fuel refers to the fuel remaining after the PHEV completes V2G. Remaining electricity refers to the remaining electricity after the PHEV completes V2G. It is the carbon emissions from the fuel consumed during the return trip; It is the carbon emissions from the electricity consumed during the return trip; E MF The carbon emissions from the fuel consumed by a plug-in hybrid electric vehicle during the time period t; E B The carbon emissions generated by plug-in hybrid electric vehicles participating in V2G and sending electrical energy back to the grid during time period t; t is time period t, and T is the total number of time periods during which plug-in hybrid electric vehicles perform energy dispatch between charging stations and the grid. This refers to the total cost of plug-in hybrid electric vehicles in a V2G energy dispatch scenario. C is the cost of fuel consumed during the return trip. MF C is the cost of fuel consumed by a plug-in hybrid electric vehicle during time period t. B The cost incurred by the plug-in hybrid electric vehicle during time period t when exchanging electrical energy with the power grid through a charging station; the return trip is the process by which the plug-in hybrid electric vehicle drives back to the owner's residence from the charging station after completing V2G.

[0028] S2. Solve for the optimal carbon emission reduction objective function and the minimum cost objective function to obtain the optimal energy scheduling strategy.

[0029] S3. Control the plug-in hybrid electric vehicle to perform energy dispatching operations according to the optimal energy dispatching strategy; wherein the energy dispatching operations include at least the plug-in hybrid electric vehicle using the fuel and / or the electrical energy to supply power to the power grid.

[0030] It is worth noting that the application scenario of the described method is vehicle-to-grid (V2G) scenarios. V2G technology refers to the technology of vehicles supplying electricity to the grid, and its core idea is to use the energy storage of a large number of vehicles as a buffer for the grid. By utilizing V2G technology, the problems of low grid efficiency and large grid load fluctuations can not only be greatly alleviated, but also generate income for vehicle owners.

[0031] Specifically, in step S1, a multi-objective function is constructed. In addition to the minimum cost objective function, an optimal carbon emission reduction objective function is added, taking into account carbon emissions under the V2G mode. In the V2G energy dispatch scenario, the main carbon emissions include: 1. Carbon emissions caused by the use of fuel to power the plug-in hybrid electric vehicle (PHEV) during its journey from the charging station back to the owner's residence after completing V2G; 2. Carbon emissions caused by the use of electricity to power the PHEV during its journey from the charging station back to the owner's residence after completing V2G; 3. Carbon emissions generated by the PHEV using fuel to feed electricity into the grid in V2G mode; 4. Carbon emissions generated by the PHEV feeding electricity back into the grid in V2G mode. In the V2G energy dispatch scenario, the main costs include, but are not limited to: 1. The fuel cost consumed by the plug-in hybrid electric vehicle during the process of driving from the charging station back to the owner's residence after completing V2G; 2. The cost of fuel consumed by the plug-in hybrid electric vehicle in supplying power to the grid at the charging station, which takes into account the revenue generated by fuel-powered electricity supply; 3. The cost incurred by the plug-in hybrid electric vehicle in exchanging electrical energy between the charging station and the grid.

[0032] Specifically, in step S2, the multi-objective function is solved to find an energy scheduling strategy that minimizes carbon emissions and costs, so that the optimal energy scheduling strategy found can limit both carbon emissions and costs to an acceptable range, avoiding situations where carbon emissions or costs are too high.

[0033] Specifically, in step S3, the optimal energy dispatch strategy is actually the control strategy for plug-in hybrid electric vehicles to supply power to the grid using fuel or electricity in V2G mode, and energy dispatch is controlled according to this strategy.

[0034] Compared with existing technologies, the method disclosed in this invention firstly constructs an optimal carbon emission reduction objective function and a minimum cost objective function in a V2G energy dispatch scenario, considering factors such as the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle (PHEV) during the return trip, the carbon emissions of electricity consumed during the return trip, the carbon emissions of fuel consumed when the PHEV performs energy dispatch with the grid, the carbon emissions generated by sending electricity back to the grid during energy dispatch, the cost of the fuel consumed during the return trip, and the cost of exchanging electricity between the PHEV and the grid. Then, by solving the multi-objective functions, an optimal energy dispatch strategy is obtained. Finally, the optimal energy dispatch strategy is used to control the PHEV's use of fuel and electricity for V2G energy dispatch with the grid, effectively reducing the carbon emissions of energy dispatch in V2G mode and contributing to environmental protection.

[0035] In a preferred embodiment, based on steps S1 to S3, the following formula is further provided: E MF =C0·Q MF ·cef MF E B =C2·Q B ·cef B ;

[0036] Among them, R MF This indicates the amount of fuel consumed during the return trip, cef. MF R represents the carbon emissions per unit of the fuel. B This indicates the amount of electrical energy consumed during the return trip, cef. B This represents the carbon emissions per unit of electrical energy; C0 represents the fuel-powered state, with a value of 1 when the fuel is used to power the grid and a value of 0 when the fuel is not used; Q MF Q represents the amount of fuel consumed during time period t; C2 represents the power supply status, with a value of 1 when the plug-in hybrid vehicle's electrical energy is used to supply power to the grid, and a value of 0 when the plug-in hybrid vehicle's electrical energy is not used to supply power to the grid. B It is the absolute value of the amount of electricity exchanged between the plug-in hybrid electric vehicle and the power grid during time period t.

[0037] Specifically, in this embodiment, the carbon emissions of the fuel consumed during the return trip are obtained by multiplying the amount of fuel consumed by the plug-in hybrid electric vehicle during the return trip by the carbon emissions per unit of fuel consumption. The carbon emissions of the fuel consumed during the return trip are obtained by multiplying the amount of electrical energy consumed by the plug-in hybrid electric vehicle during the return trip by the carbon emissions per unit of electrical energy. The carbon emissions corresponding to the method of using fuel to supply electricity to the grid are obtained by multiplying the amount of fuel consumed by the plug-in hybrid electric vehicle using fuel to supply electricity to the grid by the carbon emissions per unit of fuel consumption.

[0038] Furthermore, the fuel is a blended fuel, which is composed of electronic fuel and conventional fuel in a set ratio; the unit carbon emission of the fuel is the sum of the carbon emissions generated by consuming the conventional fuel and the carbon emissions generated by producing the electronic fuel in each unit of the blended fuel.

[0039] Specifically, plug-in hybrid electric vehicles (PHEVs) are powered by a combination of fuels and electricity. These PHEVs can supply power to the grid using both fuels and electricity. The fuels include e-fuels and conventional fuels. Conventional fuels are gasoline, while e-fuels, also known as synthetic fuels, are a transformative technology for carbon neutrality, offering a novel solution for energy transition and achieving carbon neutrality goals. E-fuels are characterized by low carbon emissions and long driving range. E-fuels are produced by catalytically reacting hydrogen (generated through water electrolysis) with carbon dioxide to create a liquid hydrocarbon chain fuel. To reduce emissions, hydrogen is obtained through water electrolysis, while carbon dioxide is collected directly from industrial waste gas or ordinary air. Therefore, the carbon emissions from e-fuel production are primarily those generated during its production. Thus, the unit carbon emission of this fuel is the carbon emission generated per unit of conventional fuel consumption plus the carbon emission generated during e-fuel production.

[0040] Furthermore, the unit carbon emissions of the electronic fuel are calculated using the following formula:

[0041] CEF e-fuel The carbon emissions per unit of the electronic fuel, cef B ηconversion represents the carbon emissions per unit of green electricity consumed in producing the electronic fuel, and ηeconversion represents the energy conversion efficiency of the electronic fuel production. I CEF represents the carbon emissions of the infrastructure required to produce one unit of electronic fuel. c CEF represents the carbon emissions required for the carbon capture process per unit of electronic fuel production. FTP represents the carbon emissions from the synthesis process required to produce one unit of electronic fuel. renewable P′ is the total amount of green electricity consumed in generating the aforementioned electronic fuel. e-fuel This refers to the total production volume of the electronic fuel;

[0042] The carbon emissions generated per unit of the blended fuel for the production of the electronic fuel are calculated based on the set ratio and the unit carbon emissions of the electronic fuel.

[0043] Specifically, the carbon emissions generated per unit of the blended fuel for producing the electronic fuel are obtained by multiplying the proportion of electronic fuel in the blended fuel by the unit carbon emissions of the electronic fuel. The unit carbon emissions of the electronic fuel are determined by the carbon emissions generated during the electronic fuel production process, and the main influencing factors include the amount of green electricity required to produce each unit of electronic fuel and the energy conversion efficiency during the electronic fuel production process. It is worth noting that a higher energy conversion efficiency will result in a lower unit carbon emissions of the electronic fuel.

[0044] Furthermore, the formula for calculating the unit carbon emissions of the electronic fuel can be set as follows:

[0045] Among them, cef o This indicates the carbon emissions from other processes required to produce electronic fuel per unit. The specific types of these other processes are set according to actual circumstances and are not limited here.

[0046] In a preferred embodiment, based on steps S1 to S3, the method further includes: C B =f B ·Q B ; f MF =P MF +C0·(-P V2G )·ε g ; f B =C1·P E +C2·(-P V2G );

[0047] Among them, f MF Q is the unit fuel cost after deducting the benefits gained by the plug-in hybrid electric vehicle from participating in V2G using the fuel. MF P is the amount of fuel consumed during time period t. MF P is the unit purchase cost of the fuel. V2G ε is the unit benefit of the plug-in hybrid electric vehicle participating in V2G. g R is the power generation efficiency of the fuel. MF f represents the amount of fuel consumed during the return trip. BP is the unit cost of electricity after deducting the benefits gained by the plug-in hybrid electric vehicle from its participation in V2G. E Q is the unit cost of electricity used to charge the plug-in hybrid electric vehicle using the charging station, and this unit cost of electricity is a time-of-use price. B Q represents the absolute value of the amount of electricity exchanged between the plug-in hybrid electric vehicle and the power grid during time period t, with a corresponding Q value for each time period t. B The values ​​are as follows: C0 represents the fuel-powered state, with a value of 1 when the fuel is used to power the grid and a value of 0 when the fuel is not used; C1 represents the vehicle-charging state, with a value of 1 when the grid is charging the plug-in hybrid electric vehicle and a value of 0 when the grid is not charging the plug-in hybrid electric vehicle; C2 represents the electrical energy-powered state, with a value of 1 when the electrical energy from the plug-in hybrid electric vehicle is used to power the grid and a value of 0 when the electrical energy from the plug-in hybrid electric vehicle is not used to power the grid.

[0048] Specifically, by determining the fuel consumption and corresponding unit cost under different conditions, the cost under different conditions can be calculated, and the total cost can be obtained by comparing all costs.

[0049] Furthermore, the fuel is a blended fuel, which is composed of conventional fuel and electronic fuel in a set ratio; the unit purchase cost of the fuel is calculated using the following formula: P MF =δP e-fuel +(1-δ)P gasoline ; P e-fuel =O e-fuel +TAX CE ; P gasoline =O gasoline +TAX CE ;

[0050] Where δ is the proportion of electronic fuel in the mixed fuel, and P e-fuel The unit cost of the electronic fuel, P, takes into account the carbon tax. gasoline The unit cost of the aforementioned traditional fuels takes into account the carbon tax. e-fuel It is the original unit cost of the electronic fuel, O gasoline The original unit cost of the conventional fuel, TAX CE This is the cost data for carbon tax.

[0051] It is worth noting that carbon tax is a tax levied on carbon dioxide emissions. It aims to mitigate global warming by reducing carbon dioxide emissions. The specific cost data of carbon tax, the proportion of traditional fuels in the blended fuel, and the proportion of electronic fuels in the blended fuel are all set according to the actual situation and are not limited here.

[0052] Specifically, using green electricity to produce E-fuel reduces the original unit cost of electronic fuel to O. e-fuel Its value can be determined in the following ways:

[0053] Considering the game theory relationship between green electricity producers and E-fuel producers, the supply and demand relationship between them reaches the Nash equilibrium condition:

[0054] In the formula, U e-fuel It is the revenue function of the E-fuel producer, P renewable It is the total amount of green electricity consumed in generating E-fuel, U renewable It is the revenue function of green electricity producers from selling green electricity;

[0055] U renewable The calculation formula is as follows: U renewable (P renewable ,α renewable D e-fuel )= R renewable (P renewable ,α renewable D e-fuel )-C renewable ×P renewable ;

[0056] In the formula, α renewable It is the proportion of renewable energy in the power structure; D e-fuel R is used to represent the relationship between the demand for E-fuel and the amount of green electricity generated, and is a function of green electricity generation; renewable C is the revenue that green electricity producers receive from selling green electricity; renewable It is used to represent the unit cost of green electricity required to produce E-fuel.

[0057] The relevant cost calculation formulas for E-fuel manufacturers are as follows: C e-fuel =(C renewable ×P renewable / ηconversion)+C e-fuel,base ;

[0058] In the formula, C e-fuel C represents the total cost of expenditure for E-fuel manufacturers.e-fuel,base The basic production cost of E-fuel is ηconversion, which is the electrical energy conversion efficiency of E-fuel production. e-fuel The carbon emissions per unit of the electronic fuel, cef B ηconversion represents the carbon emissions per unit of green electricity consumed in producing the electronic fuel, and ηeconversion represents the energy conversion efficiency of the electronic fuel production. I This indicates the carbon emissions of the infrastructure required for the electronic fuel production unit, cef. c This represents the carbon emissions from the carbon capture process required for the electronic fuel production unit, cef. FT This represents the carbon emissions (cef) required for the synthesis process of the electronic fuel produced per unit. o P represents the carbon emissions from other processes required for the production of electronic fuel per unit. renewable P′ is the total amount of green electricity consumed in generating the aforementioned electronic fuel. e-fuel This refers to the total production volume of the electronic fuel;

[0059] Set the following formula: D renewable (t′)=D e-fuel (P renewable (t′); U e-fuel (P renewable ,α renewable ) = P renewable ×O e-fuel -(C e-fuel,base + C renewable );

[0060] In the formula, D renewable (t′) represents the demand for E-fuel during time period t′, D e-fuel As a demand function, the generation of green electricity will affect the demand for E-fuel, O e-fuel The price at which E-fuel manufacturers sell E-fuel, which is the cost for electric vehicle owners to purchase and use E-fuel (i.e., the original unit cost of electronic fuel).

[0061] By using the above formula, the initial unit cost O of electronic fuel can be determined under the condition that the supply and demand relationship between green electricity producers and E-fuel producers reaches Nash equilibrium. e-fuel .

[0062] Compared with existing technologies, the V2G-based energy dispatching method provided in this invention firstly constructs an optimal carbon emission reduction objective function and a minimum cost objective function by considering factors such as the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle (PHEV) during its return trip, the carbon emissions of electricity consumed during the return trip, the carbon emissions of fuel consumed during energy dispatching between the PHEV and the grid, the carbon emissions generated by sending electricity back to the grid during energy dispatching between the PHEV and the grid, the cost of the fuel consumed during the return trip, and the cost of exchanging electricity between the PHEV and the grid. Then, by solving the multi-objective functions, an optimal energy dispatching strategy is obtained. Finally, by controlling the PHEV to perform energy dispatching operations based on its fuel and / or electricity according to the obtained optimal energy dispatching strategy, the carbon emissions of energy dispatching between the PHEV and the grid in V2G mode are effectively reduced, which is beneficial to environmental protection.

[0063] Referring to Figure 2, Figure 2 illustrates a V2G-based energy dispatching device provided in an embodiment of the present invention. The V2G-based energy dispatching device includes:

[0064] Function building module 21 is used to construct the optimal carbon reduction objective function and the minimum cost objective function:

[0065] in, It is the total carbon emissions of plug-in hybrid electric vehicles in the V2G energy dispatch scenario; It is the carbon emissions from the fuel consumed during the return trip; It is the carbon emissions from the electricity consumed during the return trip; E MF E represents the carbon emissions from the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The carbon emissions generated by the plug-in hybrid electric vehicle participating in V2G and sending electrical energy back to the grid during time period t; t is time period t, and T is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatch between the charging station and the grid. This refers to the total cost of the plug-in hybrid electric vehicle under the V2G energy dispatch scenario. C is the cost of the fuel consumed during the return trip. MF C is the cost of the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The cost incurred by the plug-in hybrid electric vehicle during time period t when exchanging electrical energy with the power grid through the charging station; the return trip is the process by which the plug-in hybrid electric vehicle returns to the owner's residence from the charging station after completing V2G.

[0066] Solver module 22 is used to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain the optimal energy scheduling strategy;

[0067] The energy dispatch module 23 is used to control the plug-in hybrid electric vehicle to perform energy dispatch operations according to the optimal energy dispatch strategy; wherein the energy dispatch operation includes at least the plug-in hybrid electric vehicle using the fuel and / or the electrical energy to supply power to the power grid.

[0068] It is worth noting that the working principle of the V2G-based energy scheduling device provided in the above embodiments can be found in the workflow of the V2G-based energy scheduling method provided in any of the above embodiments, and will not be repeated here.

[0069] Compared with existing technologies, the V2G-based energy dispatching device provided in this invention firstly constructs an optimal carbon emission reduction objective function and a minimum cost objective function under the V2G energy dispatching scenario by considering factors such as the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle (PHEV) during the return trip, the carbon emissions of electricity consumed during the return trip, the carbon emissions of fuel consumed when the PHEV performs energy dispatching with the grid, the carbon emissions generated by sending electricity back to the grid during energy dispatching with the PHEV, the cost of the fuel consumed during the return trip, and the cost incurred when the PHEV exchanges electricity with the grid. Then, by solving the multi-objective functions, an optimal energy dispatching strategy is obtained. Finally, by controlling the PHEV to perform energy dispatching operations based on the vehicle's fuel and / or electricity according to the obtained optimal energy dispatching strategy, the carbon emissions of energy dispatching between the PHEV and the grid in the V2G mode are effectively reduced, which is beneficial to environmental protection.

[0070] Referring to Figure 3, this embodiment of the invention also provides a V2G-based energy scheduling device, including a processor 31, a memory 32, and a computer program stored in the memory 32 and configured to be executed by the processor 31. When the processor 31 executes the computer program, it implements the steps as described in the above-described V2G-based energy scheduling method embodiments, such as S1 to S3 in Figure 1; or, when the processor 31 executes the computer program, it implements the functions of each module in the above-described device embodiments.

[0071] For example, the computer program may be divided into one or more modules, which are stored in the memory 32 and executed by the processor 31 to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the V2G-based energy dispatching device. For example, the computer program may be divided into multiple modules, each module being used to execute specific steps in the method described in any of the above embodiments.

[0072] The V2G-based energy dispatching device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The V2G-based energy dispatching device may include, but is not limited to, a processor 31 and a memory 32. Those skilled in the art will understand that the V2G-based energy dispatching device may also include input / output devices, network access devices, buses, etc.

[0073] The processor 31 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 31 is the control center of the V2G-based energy dispatching device, connecting all parts of the V2G-based energy dispatching device via various interfaces and lines.

[0074] The memory 32 can be used to store the computer program and / or modules. The processor 31 implements various functions of the V2G-based energy dispatching device by running or executing the computer program and / or modules stored in the memory 32 and calling the data stored in the memory 32. The memory 32 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as image playback function), etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory 32 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0075] If the V2G-based energy dispatching device integrated module is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by the processor 31, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0076] This invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the V2G-based energy scheduling method as described in any of the above embodiments.

[0077] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A V2G-based energy scheduling method, characterized in that, include: Construct the optimal carbon reduction objective function and the minimum cost objective function: in, It is the total carbon emissions of plug-in hybrid electric vehicles in the V2G energy dispatch scenario; It is the carbon emissions from the fuel consumed during the return trip; It is the carbon emissions from the electricity consumed during the return trip; E MF E represents the carbon emissions from the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The carbon emissions generated by the plug-in hybrid electric vehicle participating in V2G and sending electrical energy back to the grid during time period t; t is time period t, and T is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatch between the charging station and the grid. This refers to the total cost of the plug-in hybrid electric vehicle under the V2G energy dispatch scenario. C is the cost of the fuel consumed during the return trip. MF C is the cost of the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The cost incurred by the plug-in hybrid electric vehicle during time period t when exchanging electrical energy with the power grid through the charging station; the return trip is the process by which the plug-in hybrid electric vehicle returns to the owner's residence from the charging station after completing V2G. Solving for the optimal carbon emission reduction objective function and the minimum cost objective function yields the optimal energy scheduling strategy; The plug-in hybrid electric vehicle is controlled to perform energy dispatching operations according to the optimal energy dispatching strategy; wherein the energy dispatching operations include at least the plug-in hybrid electric vehicle using the fuel and / or the electrical energy to supply power to the power grid.

2. The V2G-based energy scheduling method as described in claim 1, characterized in that, Also includes: E MF =C0·Q MF ·cef MF ; E B =C2·Q B ·cef B ; Among them, R MF This refers to the amount of fuel consumed during the return trip, CEF. MF R is the carbon emission per unit of the fuel; B It refers to the amount of electrical energy consumed during the return trip, CEF. B Q represents the carbon emissions per unit of electricity; C0 indicates the fuel-to-grid state, with a value of 1 when the fuel is used to supply power to the grid, and a value of 0 when the fuel is not used to supply power to the grid. MF Q represents the amount of fuel consumed during time period t; C2 represents the power supply status, with a value of 1 when the plug-in hybrid vehicle's electrical energy is used to supply power to the grid, and a value of 0 when the plug-in hybrid vehicle's electrical energy is not used to supply power to the grid. B It is the absolute value of the amount of electricity exchanged between the plug-in hybrid electric vehicle and the power grid during time period t.

3. The V2G-based energy scheduling method as described in claim 2, characterized in that, The fuel is a blended fuel, which is composed of electronic fuel and conventional fuel in a set ratio; the unit carbon emission of the fuel is the sum of the carbon emissions generated by consuming the conventional fuel and the carbon emissions generated by producing the electronic fuel in each unit of the blended fuel.

4. The V2G-based energy scheduling method as described in claim 3, characterized in that, The carbon emissions per unit of the electronic fuel are calculated using the following formula: CEF e-fuel The carbon emissions per unit of the electronic fuel, cef B ηconversion represents the carbon emissions per unit of green electricity consumed in producing the electronic fuel, and ηeconversion represents the energy conversion efficiency of the electronic fuel production. I CEF represents the carbon emissions of the infrastructure required to produce one unit of electronic fuel. c CEF represents the carbon emissions required for the carbon capture process per unit of electronic fuel production. FT P represents the carbon emissions from the synthesis process required to produce one unit of electronic fuel. renewable P′ is the total amount of green electricity consumed in generating the aforementioned electronic fuel. e-fuel This refers to the total production volume of the electronic fuel; The carbon emissions generated per unit of the blended fuel for the production of the electronic fuel are calculated based on the set ratio and the unit carbon emissions of the electronic fuel.

5. The V2G-based energy scheduling method as described in claim 1, characterized in that, Also includes: C MF =f MF ·Q MF ; C B =f B ·Q B ; f MF =P MF +C0·(-P V2G )·ε g ; f B =C1·P E +C2·(-P V2G ); Among them, f MF Q is the unit fuel cost after deducting the benefits gained by the plug-in hybrid electric vehicle from participating in V2G using the fuel. MF P is the amount of fuel consumed during time period t. MF P is the unit purchase cost of the fuel. V2G ε is the unit benefit of the plug-in hybrid electric vehicle participating in V2G. g R is the power generation efficiency of the fuel. MF f represents the amount of fuel consumed during the return trip. B P is the unit cost of electricity after deducting the benefits gained by the plug-in hybrid electric vehicle from its use of electricity to participate in V2G. E Q is the unit cost of electricity used to charge the plug-in hybrid electric vehicle using the charging station. B C1 represents the absolute value of the amount of electricity exchanged between the plug-in hybrid electric vehicle (PHEV) and the power grid during time period t; C0 represents the fuel-powered state, with a value of 1 when the fuel is used to power the power grid and a value of 0 when the fuel is not used; C1 represents the vehicle-charging state, with a value of 1 when the power grid is charging the PHEV and a value of 0 when the power grid is not charging the PHEV; C2 represents the electrical energy-powered state, with a value of 1 when the electrical energy from the PHEV is used to power the power grid and a value of 0 when the electrical energy from the PHEV is not used.

6. The V2G-based energy scheduling method as described in claim 5, characterized in that, The fuel is a blended fuel, which is composed of conventional fuel and electronic fuel in a set ratio; the unit purchase cost of the fuel is calculated using the following formula: P MF =δP e-fuel +(1-δ)P gasoline ; P e-fuel =O e-fuel +TAX CE ; P gasoline =O gasoline +TAX CE ; Where δ is the proportion of electronic fuel in the mixed fuel, and P e-fuel The unit cost of the electronic fuel, P, takes into account the carbon tax. gasoline The unit cost of the aforementioned traditional fuels takes into account the carbon tax. e-fuel It is the original unit cost of the electronic fuel, O gasoline The original unit cost of the conventional fuel, TAX CE This is the cost data for carbon tax.

7. A V2G-based energy dispatching device, characterized in that, include: The function building module is used to construct the optimal carbon reduction objective function and the minimum cost objective function: in, It is the total carbon emissions of plug-in hybrid electric vehicles in the V2G energy dispatch scenario; It is the carbon emissions from the fuel consumed during the return trip; It is the carbon emissions from the electricity consumed during the return trip; E MF E represents the carbon emissions from the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The carbon emissions generated by the plug-in hybrid electric vehicle participating in V2G and sending electrical energy back to the grid during time period t; t is time period t, and T is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatch between the charging station and the grid. This refers to the total cost of the plug-in hybrid electric vehicle under the V2G energy dispatch scenario. C is the cost of the fuel consumed during the return trip. MF C is the cost of the fuel consumed by the plug-in hybrid electric vehicle during time period t. B The cost incurred by the plug-in hybrid electric vehicle during time period t when exchanging electrical energy with the power grid through the charging station; the return trip is the process by which the plug-in hybrid electric vehicle returns to the owner's residence from the charging station after completing V2G. The solution module is used to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain the optimal energy scheduling strategy; An energy dispatch module is used to control the plug-in hybrid electric vehicle to perform energy dispatch operations according to the optimal energy dispatch strategy; wherein the energy dispatch operation includes at least the plug-in hybrid electric vehicle using the fuel and / or the electrical energy to supply power to the power grid.

8. A V2G-based energy dispatching device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the V2G-based energy scheduling method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the V2G-based energy scheduling method as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the V2G-based energy scheduling method as described in any one of claims 1 to 6.

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