V2G-based energy scheduling method and device, equipment, storage medium and product

Abstract

The invention discloses an energy scheduling method and device based on V2G, equipment, a storage medium and a product. The carbon emission of fuel consumed by the plug-in hybrid electric vehicle in the return stroke process, the carbon emission of electric energy consumed by the plug-in hybrid electric vehicle in the return stroke process, the carbon emission of fuel consumed when the plug-in hybrid electric vehicle and a power grid conduct energy dispatching and the carbon emission generated when the electric energy is sent back to the power grid are considered. The optimal carbon emission reduction objective function and the minimum cost objective function are constructed according to factors such as the cost of the fuel consumed in the return stroke process and the cost consumed when the plug-in hybrid electric vehicle exchanges electric energy with a power grid; the optimal energy scheduling strategy is obtained by solving the multi-objective function, so that the plug-in hybrid electric vehicle is controlled to execute energy scheduling operation based on fuel and / or electric energy, the carbon emission of energy scheduling in the V2G mode is effectively reduced, and environmental protection is facilitated.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a V2G-based energy scheduling method, device, equipment, storage medium and product. Background Art

[0002] In recent years, with the increasing severity of global climate change and environmental pollution, as well as people's demand for vehicle endurance, plug-in hybrid electric vehicles (PHEV) have become one of the options to replace traditional fuel vehicles due to their low carbon emissions and long endurance. CATARC PHEV sales data show that the growth rates of PHEV in the past three years were 147%, 134% and 85% respectively. With the popularization of plug-in hybrid vehicles and the rapid development of vehicle-grid interaction technology, PHEV will become an important flexible energy storage resource for the power grid.

[0003] Currently, in the vehicle-to-grid (V2G) mode, the energy scheduling of vehicles transmitting electricity to the grid generally only takes economy as the optimization goal, lacks low-carbon optimization of energy scheduling, and is not conducive to environmental protection. Therefore, it is necessary to consider low-carbon emissions to achieve energy scheduling of vehicles in the V2G mode. Summary of the invention

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

[0005] To achieve the above object, an embodiment of the present invention provides a V2G-based energy scheduling method, including: Construct the optimal carbon emission reduction objective function and the minimum cost objective function: ; ; in, is the total carbon emissions of plug-in hybrid vehicles in the V2G energy dispatch scenario; is the carbon emission of the fuel consumed during the return trip; is the carbon emissions of the electricity consumed during the return trip; It is the time period the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle; It is the time period The carbon emissions generated by the plug-in hybrid vehicle participating in V2G and sending electricity back to the grid; It is the time period , is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatching between the charging pile and the power grid; is the total cost of the plug-in hybrid vehicle in the V2G energy scheduling scenario, is the cost of the fuel consumed during the return trip, It is the time period the cost of the fuel consumed by the plug-in hybrid electric vehicle, It is the time period The cost consumed by the plug-in hybrid electric vehicle in exchanging electric energy with the power grid through the charging pile; the return trip process is the process of the plug-in hybrid electric vehicle driving from the charging pile back to the owner's residence after completing V2G; Solving the optimal carbon emission reduction objective function and the minimum cost objective function to obtain an optimal energy scheduling strategy; The plug-in hybrid electric vehicle is controlled to perform an energy scheduling operation according to the optimal energy scheduling strategy; wherein the energy scheduling operation at least includes the plug-in hybrid electric vehicle using the fuel and / or the electric energy to supply electricity to the power grid.

[0006] To achieve the above object, an embodiment of the present invention further provides a V2G-based energy scheduling device, including: Function building module, used to build the optimal carbon reduction objective function and the minimum cost objective function: ; ; in, is the total carbon emissions of plug-in hybrid vehicles in the V2G energy dispatch scenario; is the carbon emission of the fuel consumed during the return trip; is the carbon emissions of the electricity consumed during the return trip; It is the time period the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle; It is the time period The carbon emissions generated by the plug-in hybrid vehicle participating in V2G and sending electricity back to the grid; It is the time period , is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatching between the charging pile and the power grid; is the total cost of the plug-in hybrid vehicle in the V2G energy scheduling scenario, is the cost of the fuel consumed during the return trip, It is the time period the cost of the fuel consumed by the plug-in hybrid electric vehicle, It is the time period The cost consumed by the plug-in hybrid electric vehicle in exchanging electric energy with the power grid through the charging pile; the return trip process is the process of the plug-in hybrid electric vehicle driving from the charging pile back to the owner's residence after completing V2G; A solution module, used to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain an optimal energy scheduling strategy; An energy scheduling module is used to control the plug-in hybrid electric vehicle to perform energy scheduling operations according to the optimal energy scheduling strategy; wherein the energy scheduling operations at least include the plug-in hybrid electric vehicle using the fuel and / or the electric energy to supply electricity to the power grid.

[0007] To achieve the above objectives, an embodiment of the present invention further provides a V2G-based energy scheduling device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the V2G-based energy scheduling method as described in any of the above embodiments is implemented.

[0008] To achieve the above objectives, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the V2G-based energy scheduling method as described in any of the above embodiments.

[0009] To achieve the above objectives, an embodiment of the present invention further 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.

[0010] Compared with the prior art, the V2G-based energy scheduling method, device, equipment, storage medium and product disclosed in the embodiments of the present invention, firstly, in the V2G energy scheduling scenario, by considering the carbon emissions of the fuel consumed by the plug-in hybrid electric vehicle during the return trip, the carbon emissions of the electric energy consumed during the return trip, the carbon emissions of the fuel consumed when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the carbon emissions generated by sending electric energy back to the power grid when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the cost of the fuel consumed during the return trip, and the cost consumed when the plug-in hybrid electric vehicle exchanges electric energy with the power grid, etc., to construct an optimal carbon emission reduction objective function and a minimum cost objective function; then, by solving the multi-objective function, an optimal energy scheduling strategy is obtained; finally, by controlling the plug-in hybrid electric vehicle to perform energy scheduling operations based on the fuel and / or electric energy of the vehicle according to the optimal energy scheduling strategy obtained by the solution, the carbon emissions of energy scheduling between the plug-in hybrid electric vehicle and the power grid in the V2G mode are effectively reduced, which is beneficial to environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the implementation mode will be briefly introduced below. Obviously, the drawings described below are only some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0012] Figure 1 It is a flowchart of a V2G-based energy scheduling method provided by an embodiment of the present invention; Figure 2 is a structural schematic diagram of a V2G-based energy scheduling device provided by an embodiment of the present invention; Figure 3 It is a structural diagram of a V2G-based energy scheduling device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] An embodiment of the present invention provides a V2G-based energy scheduling method, see Figure 1The schematic diagram of the process of the V2G-based energy scheduling method is shown in FIG. Specifically, the V2G-based energy scheduling method includes steps S1 to S3: S1. Construct the optimal carbon emission reduction objective function and the minimum cost objective function.

[0015] The optimal carbon emission reduction objective function and the minimum cost objective function are as follows: ; ; in, is the total carbon emissions of plug-in hybrid electric vehicles in the V2G energy dispatch scenario, where Is the plug-in hybrid vehicle in the period The absolute value of the amount of electricity exchanged with the grid, subscript It is the time period The amount of fuel consumed, subscript To reflect the variables of vehicle mode, vehicle mode includes vehicle charging mode (G2V), power transmission mode (electricity V2G) and fuel transmission mode (oil V2G). Vehicle charging mode refers to the grid charging plug-in hybrid vehicles, power transmission mode refers to the use of plug-in hybrid vehicle electricity to transmit electricity to the grid, and fuel transmission mode refers to the use of plug-in hybrid vehicle fuel to transmit electricity to the grid. is the ratio of the fuel consumed in the return trip at the last moment to the remaining fuel, It is the ratio of the electric energy consumed for the return trip at the last moment to the remaining electric energy. The remaining fuel refers to the remaining fuel after the plug-in hybrid vehicle completes V2G, and the remaining electric energy refers to the remaining electric energy after the plug-in hybrid vehicle completes V2G; is the carbon emission of the fuel consumed during the return trip; is the carbon emissions of the electricity consumed during the return trip; It is the time period the carbon emissions of the fuel consumed by the plug-in hybrid vehicle; It is the time period Carbon emissions from plug-in hybrid vehicles participating in V2G and sending electricity back to the grid; It is the time period , is the total number of time periods during which plug-in hybrid vehicles perform energy dispatch between charging piles and the grid; is the total cost of a plug-in hybrid vehicle in a V2G energy dispatch scenario, is the cost of the fuel consumed during the return trip, It is the time period The cost of the fuel consumed by the plug-in hybrid vehicle, It is the time period The cost consumed by the plug-in hybrid electric vehicle to exchange electric energy with the power grid through the charging pile; the return process is the process of the plug-in hybrid electric vehicle driving from the charging pile back to the owner's home after completing V2G.

[0016] S2. Solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain the optimal energy scheduling strategy.

[0017] S3. Controlling the plug-in hybrid electric vehicle to perform an energy scheduling operation according to the optimal energy scheduling strategy; wherein the energy scheduling operation at least includes the plug-in hybrid electric vehicle using the fuel and / or the electric energy to supply electricity to the power grid.

[0018] It is worth noting that the application scenario of the method is the vehicle-to-grid (V2G) scenario. V2G technology refers to the technology of vehicles transmitting electricity to the grid. Its core idea is to use the energy storage of a large number of vehicles as a buffer for the grid. By using V2G technology, the problems of low grid efficiency and large grid load fluctuations can not only be alleviated to a great extent, but also generate income for car owners.

[0019] Specifically, in step S1, a multi-objective function is constructed. In addition to the minimum cost objective function, an optimal carbon reduction objective function is added to take into account the carbon emissions in the V2G mode. In the V2G energy scheduling scenario, the main carbon emissions include: 1. The carbon emissions caused by the use of fuel to power the plug-in hybrid vehicle in the process of driving from the charging pile back to the owner's residence after completing V2G, 2. The carbon emissions caused by the use of electricity to power the plug-in hybrid vehicle in the process of driving from the charging pile back to the owner's residence after completing V2G, 3. The carbon emissions generated by the plug-in hybrid vehicle using fuel to send electricity to the power grid in the V2G mode, 4. The carbon emissions generated by the plug-in hybrid vehicle sending electricity back to the power grid in the V2G mode. In the V2G energy scheduling scenario, the main costs include but are not limited to: 1. The cost of fuel consumed by the plug-in hybrid vehicle when driving from the charging station back to the owner's home after completing V2G; 2. The cost of fuel consumed by the plug-in hybrid vehicle when the charging station supplies electricity to the grid, which is the cost after considering the income generated by fuel power transmission; 3. The cost generated by the plug-in hybrid vehicle when exchanging electricity between the charging station and the grid.

[0020] Specifically, in step S2, the multi-objective function is solved to find an energy scheduling strategy that reduces carbon emissions and costs as much as possible, so that the optimal energy scheduling strategy found can limit both carbon emissions and costs to an acceptable range, avoiding excessive carbon emissions or excessive costs.

[0021] Specifically, in step S3, the optimal energy dispatch strategy is actually a control strategy for the plug-in hybrid vehicle to transmit electricity to the power grid using fuel or electric energy in the V2G mode, and the energy dispatch is controlled according to the strategy.

[0022] Compared with the prior art, the method disclosed in the embodiment of the present invention firstly constructs an optimal carbon emission reduction objective function and a minimum cost objective function in a V2G energy scheduling scenario by considering factors such as the carbon emissions of the fuel consumed by the plug-in hybrid electric vehicle during the return trip, the carbon emissions of the electric energy consumed during the return trip, the carbon emissions of the fuel consumed when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the carbon emissions generated by sending electric energy back to the power grid when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the cost of the fuel consumed during the return trip, and the cost consumed when the plug-in hybrid electric vehicle exchanges electric energy with the power grid; then, the optimal energy scheduling strategy is obtained by solving the multi-objective function; finally, the plug-in hybrid electric vehicle is controlled to use fuel and electric energy according to the optimal energy scheduling strategy obtained by the solution, and V2G energy scheduling is performed with the power grid, thereby effectively reducing the carbon emissions of energy scheduling in the V2G mode, which is beneficial to environmental protection.

[0023] In a preferred embodiment, based on steps S1 to S3, the following formula is further set: ; ; ; ; in, Indicates the amount of fuel consumed during the return trip. Indicates the specific carbon emissions of the fuel; Indicates the amount of electrical energy consumed during the return journey. Indicates the carbon emissions per unit of electricity; Indicates the fuel power supply status. When the fuel is used to supply power to the grid The value is 1 when the fuel is not used to supply electricity to the grid. The value of is 0; Indicates time period The amount of fuel consumed; Indicates the power transmission state, when the power of the plug-in hybrid vehicle is used to transmit power to the grid The value of is 1, when the electric energy of the plug-in hybrid vehicle is not used to supply electricity to the grid The value of is 0, Is the plug-in hybrid electric vehicle in the period The absolute value of the amount of electricity exchanged with the grid.

[0024] Specifically, in this embodiment, the carbon emissions of the fuel consumed during the return trip are obtained by multiplying the obtained amount of fuel consumed by the plug-in hybrid electric vehicle during the return trip with the unit carbon emissions of the fuel. The carbon emissions of the fuel consumed during the return trip are obtained by multiplying the obtained amount of electric energy consumed by the plug-in hybrid electric vehicle during the return trip with the unit carbon emissions of the electric energy. The carbon emissions corresponding to the method of using fuel to transmit electricity to the grid are obtained by multiplying the obtained amount of fuel consumed by the plug-in hybrid electric vehicle using fuel with the unit carbon emissions of the fuel.

[0025] Furthermore, the fuel is a mixed fuel, which is composed of electronic fuel and traditional fuel according to a set ratio; the unit carbon emissions of the fuel are the sum of the carbon emissions generated by consuming the traditional fuel and the carbon emissions generated for producing the electronic fuel in each unit of the mixed fuel.

[0026] Specifically, a hybrid fuel and electric energy are used to power plug-in hybrid electric vehicles. Plug-in hybrid electric vehicles can use a hybrid fuel and electric energy to deliver electricity to the power grid. The hybrid fuel includes electronic fuel and traditional fuel. The traditional fuel is gasoline, and the electronic fuel is E-fuel, also known as synthetic fuel. Electronic fuel is a transformative technology for carbon neutrality, providing a new solution for energy transformation and the realization of carbon neutrality goals. It has the characteristics of low carbon emissions and high endurance. Electronic fuel is a liquid hydrocarbon chain fuel generated by the catalytic reaction of hydrogen generated by water electrolysis and carbon dioxide. In the process of generating electronic fuel, in order to reduce emission indicators, hydrogen is obtained by "electrolysis of water", and carbon dioxide is directly collected from industrial waste gas or ordinary air. It can be seen that the carbon emissions generated by electronic fuel are mainly the carbon emissions generated by the production of electronic fuel. Therefore, the unit carbon emissions of the fuel are the carbon emissions generated by the consumption of traditional fuel per unit of the mixed fuel, plus the carbon emissions generated by the production of electronic fuel.

[0027] Furthermore, the unit carbon emission of the electronic fuel is calculated by the following formula: ; ; represents the unit carbon emission of the electronic fuel, Indicates the unit carbon emission of green electricity consumed to produce the electronic fuel, represents the electric energy conversion efficiency of the electronic fuel production, represents the carbon emissions of the infrastructure required to produce a unit of e-fuel, represents the carbon emissions from the carbon capture process required to produce a unit of electronic fuel, represents the carbon emissions of the synthesis process required to produce a unit of electronic fuel, is the total amount of green electricity consumed to generate the electronic fuel, is the total production of said electronic fuel; The carbon emission amount generated for producing the electronic fuel in each unit of the mixed fuel is calculated based on the set ratio and the unit carbon emission amount of the electronic fuel.

[0028] Specifically, the carbon emissions generated for producing the electronic fuel per unit of the mixed fuel are obtained by multiplying the proportion of the electronic fuel in the mixed 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 in the process of generating the electronic fuel. The main influencing factors include the amount of green electricity required to generate each unit of electronic fuel and the power conversion efficiency when generating the electronic fuel. It is worth noting that as the power conversion efficiency increases, the unit carbon emissions of the electronic fuel will decrease accordingly.

[0029] Furthermore, the calculation formula of the unit carbon emission of the electronic fuel can also be set as: ; in, It represents the carbon emissions of other processes required to produce a unit of electronic fuel. The specific types of other processes are set according to actual conditions and are not limited here.

[0030] In a preferred embodiment, based on steps S1 to S3, the method further includes: ; ; ; ; ; in, is the unit cost of fuel after deducting the profit obtained by the plug-in hybrid vehicle from using the fuel to participate in V2G, It is the time period The amount of fuel consumed, is the unit purchase cost of the fuel, is the unit benefit of the plug-in hybrid vehicle participating in V2G, is the power generation efficiency of the fuel, Indicates the amount of fuel consumed during the return trip. is the unit cost of electricity after deducting the profit obtained by the plug-in hybrid vehicle using electricity to participate in V2G, is the unit electricity cost when the plug-in hybrid electric vehicle is charged using the charging pile, and the unit electricity cost is a time-sharing price. Indicates that the plug-in hybrid vehicle is The absolute value of the amount of electricity exchanged with the grid, per period There are corresponding value, Indicates the fuel power supply status. When the fuel is used to supply power to the grid The value is 1 when the fuel is not used to supply electricity to the grid. The value of is 0; Indicates the vehicle charging state, when the power grid is charging the plug-in hybrid vehicle The value of is 1, when the power grid is not charging the plug-in hybrid vehicle The value of is 0; Indicates the power transmission state, when the power of the plug-in hybrid vehicle is used to transmit power to the grid The value of is 1, when the electric energy of the plug-in hybrid vehicle is not used to supply electricity to the grid The value of is 0.

[0031] Specifically, by determining the fuel consumption under different conditions and the corresponding unit cost, the cost under different conditions is calculated, and the total cost can be obtained by comparing all the costs.

[0032] Furthermore, the fuel is a mixed fuel, which is composed of traditional fuel and electronic fuel according to a set ratio; the unit purchase cost of the fuel is calculated by the following formula: ; ; ; in, is the proportion of the electronic fuel in the mixed fuel, is the unit cost of the e-fuel taking into account the carbon tax, is the unit cost of the conventional fuel taking into account the carbon tax, is the original unit cost of the electronic fuel, is the original unit cost of the conventional fuel, Cost data for carbon taxes.

[0033] It is worth explaining that carbon tax refers to a tax levied on carbon dioxide emissions. It aims at environmental protection and hopes to slow down global warming by reducing carbon dioxide emissions. The specific values ​​of the carbon tax cost data, the proportion of traditional fuel in the mixed fuel, and the proportion of electronic fuel in the mixed fuel are all set according to actual conditions and are not limited here.

[0034] Specifically, using green electricity to produce E-fuel, the original unit cost of electronic fuel is The value can be determined in the following ways: Considering the game relationship between green electricity producers and E-fuel producers, the supply and demand relationship between green electricity producers and E-fuel producers reaches the Nash equilibrium condition: ; ; In the formula, is the revenue function of the E-fuel producer, is the total amount of green electricity consumed to generate E-fuel, is the revenue function of green electricity sales of green electricity producers; The calculation formula is as follows: = ; In the formula, is the proportion of renewable energy in the electricity mix; It is used to express the relationship between the demand for E-fuel and the amount of green electricity generated, which is a function of the amount of green electricity generated; It is the income that green electricity producers get from selling green electricity; Used to indicate the unit cost of green electricity required to produce E-fuel.

[0035] The relevant cost calculation formula for E-fuel producers is as follows: ; ; ; In the formula, represents the total cost of expenditure of E-fuel producers, It is the basic production cost of producing E-fuel. is the conversion efficiency of the electric energy produced by E-fuel, represents the unit carbon emission of the electronic fuel, Indicates the unit carbon emission of green electricity consumed to produce the electronic fuel, represents the electric energy conversion efficiency of the electronic fuel production, represents the carbon emissions of the infrastructure required to produce the unit of electronic fuel, represents the carbon emissions from the carbon capture process required to produce a unit of electronic fuel, represents the carbon emissions of the synthesis process required to produce a unit of electronic fuel, represents the carbon emissions of other processes required to produce a unit of electronic fuel, is the total amount of green electricity consumed to generate the electronic fuel, is the total production of said electronic fuel; Set up the following formula: ; ; In the formula, for The demand for E-fuel in the time period, As a demand function, the amount of green electricity generated will affect the demand for E-fuel. The price at which E-fuel is sold by E-fuel producers, that is, the cost for electric car owners to purchase and use E-fuel (that is, the original unit cost of electronic fuel).

[0036] By using the above formula, the original unit cost of E-fuel is determined when the supply and demand relationship between green electricity producers and E-fuel producers reaches the Nash equilibrium condition. .

[0037] Compared with the prior art, the V2G-based energy scheduling method provided in the embodiment of the present invention firstly, in the V2G energy scheduling scenario, by considering the carbon emissions of the fuel consumed by the plug-in hybrid electric vehicle during the return trip, the carbon emissions of the electric energy consumed during the return trip, the carbon emissions of the fuel consumed when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the carbon emissions generated by sending electric energy back to the power grid when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the cost of the fuel consumed during the return trip, and the cost consumed when the plug-in hybrid electric vehicle exchanges electric energy with the power grid, etc., to construct an optimal carbon emission reduction objective function and a minimum cost objective function; then, by solving the multi-objective function, an optimal energy scheduling strategy is obtained; finally, by controlling the plug-in hybrid electric vehicle to perform energy scheduling operations based on the fuel and / or electric energy of the vehicle according to the optimal energy scheduling strategy obtained by the solution, the carbon emissions of energy scheduling between the plug-in hybrid electric vehicle and the power grid in the V2G mode are effectively reduced, which is beneficial to environmental protection.

[0038] See also Figure 2 , Figure 2 An energy scheduling device based on V2G is provided in an embodiment of the present invention. The energy scheduling device based on V2G includes: Function construction module 21 is used to construct the optimal carbon emission reduction objective function and the minimum cost objective function: ; ; in, is the total carbon emissions of plug-in hybrid vehicles in the V2G energy dispatch scenario; is the carbon emission of the fuel consumed during the return trip; is the carbon emissions of the electricity consumed during the return trip; It is the time period the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle; It is the time period The carbon emissions generated by the plug-in hybrid vehicle participating in V2G and sending electricity back to the grid; It is the time period , is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatching between the charging pile and the power grid; is the total cost of the plug-in hybrid vehicle in the V2G energy scheduling scenario, is the cost of the fuel consumed during the return trip, It is the time period the cost of the fuel consumed by the plug-in hybrid electric vehicle, It is the time period The cost consumed by the plug-in hybrid electric vehicle in exchanging electric energy with the power grid through the charging pile; the return trip process is the process of the plug-in hybrid electric vehicle driving from the charging pile back to the owner's residence after completing V2G; A solution module 22, used to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain an optimal energy scheduling strategy; The energy scheduling module 23 is used to control the plug-in hybrid electric vehicle to perform energy scheduling operations according to the optimal energy scheduling strategy; wherein the energy scheduling operations at least include the plug-in hybrid electric vehicle using the fuel and / or the electric energy to supply electricity to the power grid.

[0039] It is worth noting that the working principle of the V2G-based energy scheduling device provided in the above embodiment can refer to the working process of the V2G-based energy scheduling method provided in any of the above embodiments, which will not be described in detail here.

[0040] Compared with the prior art, the V2G-based energy scheduling device provided in the embodiment of the present invention, firstly, in the V2G energy scheduling scenario, by considering the carbon emissions of the fuel consumed by the plug-in hybrid electric vehicle during the return trip, the carbon emissions of the electric energy consumed during the return trip, the carbon emissions of the fuel consumed when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the carbon emissions generated by sending electric energy back to the power grid when the plug-in hybrid electric vehicle performs energy scheduling with the power grid, the cost of the fuel consumed during the return trip, and the cost consumed when the plug-in hybrid electric vehicle exchanges electric energy with the power grid, etc., to construct an optimal carbon emission reduction objective function and a minimum cost objective function; then, by solving the multi-objective function, an optimal energy scheduling strategy is obtained; finally, by controlling the plug-in hybrid electric vehicle to perform energy scheduling operations based on the fuel and / or electric energy of the vehicle according to the optimal energy scheduling strategy obtained by the solution, the carbon emissions of energy scheduling between the plug-in hybrid electric vehicle and the power grid in the V2G mode are effectively reduced, which is beneficial to environmental protection.

[0041] See also Figure 3 The embodiment of the present invention further 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, the steps in the above-mentioned V2G-based energy scheduling method embodiment are implemented, for example Figure 1 S1~S3 in; or, the processor 31 implements the functions of each module in the above-mentioned device embodiments when executing the computer program.

[0042] Exemplarily, the computer program may be divided into one or more modules, and the one or more modules 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 completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the V2G-based energy scheduling device. For example, the computer program may be divided into multiple modules, each of which is used to execute the specific steps in the method described in any of the above embodiments.

[0043] The V2G-based energy scheduling device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The V2G-based energy scheduling device may include, but is not limited to, a processor 31 and a memory 32. Those skilled in the art may understand that the V2G-based energy scheduling device may also include input and output devices, network access devices, buses, etc.

[0044] The processor 31 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor 31 is the control center of the V2G-based energy dispatching device, and uses various interfaces and lines to connect various parts of the entire V2G-based energy dispatching device.

[0045] The memory 32 can be used to store the computer program and / or module. The processor 31 realizes various functions of the V2G-based energy scheduling device by running or executing the computer program and / or module stored in the memory 32 and calling the data stored in the memory 32. The memory 32 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory 32 can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0046] Wherein, if the module integrated by the V2G-based energy scheduling device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor 31, the steps of the above-mentioned method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0047] An embodiment of the present invention further 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.

[0048] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. 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 emission reduction objective function and the minimum cost objective function: ； ； in, is the total carbon emissions of plug-in hybrid vehicles in the V2G energy dispatch scenario; is the carbon emissions of the fuel consumed during the return trip; is the carbon emissions of the electricity consumed during the return trip; It is the time period the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle; It is the time period The carbon emissions generated by the plug-in hybrid vehicle participating in V2G and sending electricity back to the grid; It is the time period , is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatching between the charging pile and the power grid; is the total cost of the plug-in hybrid vehicle in the V2G energy scheduling scenario, is the cost of the fuel consumed during the return trip, It is the time period the cost of the fuel consumed by the plug-in hybrid electric vehicle, It is the time period The cost consumed by the plug-in hybrid electric vehicle in exchanging electric energy with the power grid through the charging pile; the return trip process is the process of the plug-in hybrid electric vehicle driving from the charging pile back to the owner's residence after completing V2G; Solving the optimal carbon emission reduction objective function and the minimum cost objective function to obtain an optimal energy scheduling strategy; The plug-in hybrid electric vehicle is controlled to perform an energy scheduling operation according to the optimal energy scheduling strategy; wherein the energy scheduling operation at least includes the plug-in hybrid electric vehicle using the fuel and / or the electric energy to supply electricity to the power grid.

2. The V2G-based energy scheduling method according to claim 1, characterized in that: Also includes: ； ； ； ； in, is the amount of fuel consumed during the return trip, is the specific carbon emission of the fuel in question; is the amount of electrical energy consumed during the return journey. is the carbon emissions per unit of electricity; Indicates the fuel power supply status. When the fuel is used to supply power to the grid The value is 1 when the fuel is not used to supply electricity to the grid. The value of is 0, It is the time period The amount of fuel consumed; Indicates the power transmission state, when the power of the plug-in hybrid vehicle is used to transmit power to the grid The value of is 1, when the electric energy of the plug-in hybrid vehicle is not used to supply electricity to the grid The value of is 0, Is the plug-in hybrid electric vehicle in the period The absolute value of the amount of electricity exchanged with the grid.

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

4. The V2G-based energy scheduling method according to claim 3, characterized in that: The unit carbon emission of the electronic fuel is calculated by the following formula: ； ； represents the unit carbon emission of the electronic fuel, Indicates the unit carbon emission of green electricity consumed to produce the electronic fuel, represents the electric energy conversion efficiency of the electronic fuel production, represents the carbon emissions of the infrastructure required to produce a unit of electronic fuel, represents the carbon emissions from the carbon capture process required to produce a unit of electronic fuel, represents the carbon emissions of the synthesis process required to produce a unit of electronic fuel, is the total amount of green electricity consumed to generate the electronic fuel, is the total production of said electronic fuel; The carbon emission amount generated for producing the electronic fuel in each unit of the mixed fuel is calculated based on the set ratio and the unit carbon emission amount of the electronic fuel.

5. The V2G-based energy scheduling method according to claim 1, characterized in that: Also includes: ； ； ； ； ； in, is the unit cost of fuel after deducting the profit obtained by the plug-in hybrid vehicle from using the fuel to participate in V2G, It is the time period The amount of fuel consumed, is the unit purchase cost of the fuel, is the unit benefit of the plug-in hybrid vehicle participating in V2G, is the power generation efficiency of the fuel, Indicates the amount of fuel consumed during the return trip. is the unit cost of electricity after deducting the profit obtained by the plug-in hybrid vehicle using electricity to participate in V2G, is the unit electricity cost when the plug-in hybrid electric vehicle is charged using the charging pile, Indicates that the plug-in hybrid vehicle is the absolute value of the amount of electricity exchanged with the grid; Indicates the fuel power supply status. When the fuel is used to supply power to the grid The value is 1 when the fuel is not used to supply electricity to the grid. The value of is 0; Indicates the vehicle charging state. When the power grid is charging the plug-in hybrid vehicle The value of is 1, when the power grid is not charging the plug-in hybrid vehicle The value of is 0; Indicates the power transmission state, when the power of the plug-in hybrid vehicle is used to transmit power to the grid The value of is 1, when the electric energy of the plug-in hybrid vehicle is not used to supply electricity to the grid The value of is 0.

6. The V2G-based energy scheduling method according to claim 5, characterized in that: The fuel is a mixed fuel, which is composed of traditional fuel and electronic fuel according to a set ratio; the unit purchase cost of the fuel is calculated by the following formula: ； ； ; in, is the proportion of the electronic fuel in the mixed fuel, is the unit cost of the e-fuel taking into account the carbon tax, is the unit cost of the conventional fuel taking into account the carbon tax, is the original unit cost of the electronic fuel, is the original unit cost of the conventional fuel, Cost data for carbon taxes.

7. A V2G-based energy scheduling device, characterized in that: include: Function building module, used to build the optimal carbon reduction objective function and the minimum cost objective function: ； ； in, is the total carbon emissions of plug-in hybrid vehicles in the V2G energy dispatch scenario; is the carbon emission of the fuel consumed during the return trip; is the carbon emissions of the electricity consumed during the return trip; It is the time period the carbon emissions of fuel consumed by the plug-in hybrid electric vehicle; It is the time period The carbon emissions generated by the plug-in hybrid vehicle participating in V2G and sending electricity back to the grid; It is the time period , is the total number of time periods during which the plug-in hybrid electric vehicle performs energy dispatching between the charging pile and the power grid; is the total cost of the plug-in hybrid vehicle in the V2G energy scheduling scenario, is the cost of the fuel consumed during the return trip, It is the time period the cost of the fuel consumed by the plug-in hybrid electric vehicle, It is the time period The cost consumed by the plug-in hybrid electric vehicle in exchanging electric energy with the power grid through the charging pile; the return trip process is the process of the plug-in hybrid electric vehicle driving from the charging pile back to the owner's residence after completing V2G; A solution module, used to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain an optimal energy scheduling strategy; An energy scheduling module is used to control the plug-in hybrid electric vehicle to perform energy scheduling operations according to the optimal energy scheduling strategy; wherein the energy scheduling operations at least include the plug-in hybrid electric vehicle using the fuel and / or the electric energy to supply electricity to the power grid.

8. A V2G-based energy scheduling device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the V2G-based energy scheduling method according to any one of claims 1 to 6 is implemented.

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, the device where the computer-readable storage medium is located is controlled to execute the V2G-based energy scheduling method according to 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 a processor, the V2G-based energy scheduling method as described in any one of claims 1 to 6 is implemented.

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