V2G-Based Energy Scheduling Method, Device, Equipment, Storage Medium and Product

Abstract

The present invention discloses an energy scheduling method, device, equipment, storage medium and product based on V2G. In the V2G energy scheduling scenario, by considering factors such as the carbon emissions of the fuel consumed by a plug-in hybrid vehicle during the return journey, the carbon emissions of the electric energy consumed during the return journey, the carbon emissions of the fuel consumed when the plug-in hybrid vehicle conducts energy scheduling with the power grid, the carbon emissions generated when sending electric energy back to the power grid, the cost of the fuel consumed during the return journey, and the cost consumed when the plug-in hybrid vehicle exchanges electric energy with the power grid, an optimal carbon emission reduction objective function and a minimum cost objective function are constructed; by solving the multi-objective function, an optimal energy scheduling strategy is obtained to control the plug-in hybrid vehicle to perform energy scheduling operations based on fuel and / or electric energy, effectively reducing the carbon emissions of energy scheduling in the V2G mode and being beneficial to environmental protection.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicles, and specifically, to an energy scheduling method, device, equipment, storage medium and product based on V2G. Background Art

[0002] In recent years, with the increasingly serious problems of global climate change and environmental pollution, as well as people's demand for the endurance of vehicles, plug-in hybrid electric vehicles (PHEVs) have become one of the choices to replace traditional fuel vehicles due to their characteristics of low carbon emissions and high endurance. The sales data of PHEVs from the China Automotive Technology and Research Center shows that the growth rates of PHEVs in the past three years are 147%, 134% and 85% respectively. With the popularization of plug-in hybrid electric vehicles and the rapid development of vehicle-to-grid interaction technology, PHEVs will become an important flexible energy storage resource for the power grid.

[0003] Currently, in the vehicle-to-grid (V2G) mode, for the energy scheduling of vehicles transmitting power to the grid, the optimization goal is generally only economic, lacking low-carbon optimization of energy scheduling, which is not conducive to environmental protection. Therefore, it is necessary to consider low-carbon emissions to achieve the energy scheduling of vehicles in the V2G mode. Summary of the Invention

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

[0005] To achieve the above object, an embodiment of the present invention provides an energy scheduling method based on V2G, including:

[0006] Construct an optimal carbon emission reduction objective function and a minimum cost objective function:

[0007] ;

[0008] ;

[0009] Wherein, is the total carbon emission of the plug-in hybrid electric vehicle in the V2G energy scheduling scenario; is the carbon emission of the fuel consumed during the return journey; is the carbon emission of the electric energy consumed during the return journey; is the carbon emission of the fuel consumed by the plug-in hybrid electric vehicle in time period ; is the carbon emission of the fuel consumed by the plug-in hybrid electric vehicle in time period The carbon emissions generated when the plug-in hybrid vehicle participates in V2G and sends electrical energy back to the power grid; is the time period , is the total number of time periods during which the plug-in hybrid vehicle conducts energy scheduling 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 journey, is the time period the cost of the fuel consumed by the plug-in hybrid vehicle, is the time period the cost consumed by the plug-in hybrid vehicle for electrical energy exchange with the power grid through the charging pile; the return journey is the process in which the plug-in hybrid vehicle drives back to the owner's residence from the charging pile after completing V2G;

[0010] Solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain the optimal energy scheduling strategy;

[0011] Control the plug-in hybrid 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 vehicle using the fuel and / or the electrical energy to send power to the power grid.

[0012] To achieve the above object, an embodiment of the present invention also provides an energy scheduling device based on V2G, including:

[0013] A function construction module for constructing an optimal carbon emission reduction objective function and a minimum cost objective function:

[0014] ;

[0015] ;

[0016] wherein, is the total carbon emissions of the plug-in hybrid vehicle in the V2G energy scheduling scenario; is the carbon emissions of the fuel consumed during the return journey; is the carbon emissions of the electrical energy consumed during the return journey; is the time period the carbon emissions of the fuel consumed by the plug-in hybrid vehicle; is the time period the carbon emissions generated when the plug-in hybrid vehicle participates in V2G and sends electrical energy back to the power grid; is the time period , is the total number of time periods during which the plug-in hybrid vehicle conducts energy scheduling 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 journey, is the time period the cost of the fuel consumed by the plug-in hybrid vehicle, is the time period the cost consumed by the plug-in hybrid vehicle for power exchange with the power grid through the charging pile; the return journey is the process in which the plug-in hybrid vehicle drives back to the owner's residence from the charging pile after completing V2G;

[0017] A solution module, configured to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain an optimal energy scheduling strategy;

[0018] An energy scheduling module, configured to control the plug-in hybrid 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 vehicle using the fuel and / or the electric energy to supply power to the power grid.

[0019] To achieve the above object, an embodiment of the present invention further provides an energy scheduling device based on V2G, 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 energy scheduling method based on V2G as described in any one of the above embodiments.

[0020] To achieve the above object, an embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the energy scheduling method based on V2G as described in any one of the above embodiments.

[0021] To achieve the above object, an embodiment of the present invention further provides a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, they implement the energy scheduling method based on V2G as described in any one of the above embodiments.

[0022] Compared with the prior art, the energy scheduling method, device, equipment, storage medium and product based on V2G 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 vehicle during the return journey, the carbon emissions of the electric energy consumed during the return journey, the carbon emissions of the fuel consumed when the plug-in hybrid vehicle conducts energy scheduling with the power grid, the carbon emissions generated when the plug-in hybrid vehicle sends electric energy back to the power grid during energy scheduling with the power grid, the cost of the fuel consumed during the return journey, and the cost consumed when the plug-in hybrid vehicle exchanges electric energy with the power grid and other factors, to construct an optimal carbon emission reduction objective function and a minimum cost objective function; then, by solving the multi-objective function to obtain an optimal energy scheduling strategy; finally, by controlling the plug-in hybrid vehicle to perform energy scheduling operations based on the vehicle's fuel and / or electric energy according to the obtained optimal energy scheduling strategy, effectively reducing the carbon emissions of energy scheduling between the plug-in hybrid vehicle and the power grid in the V2G mode, which is beneficial to environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 is a flowchart of an energy scheduling method based on V2G provided by an embodiment of the present invention;

[0025] Figure 2 is a structural diagram of an energy scheduling device based on V2G provided by an embodiment of the present invention;

[0026] Figure 3 is a structural diagram of an energy scheduling equipment based on V2G provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0028] An embodiment of the present invention provides an energy scheduling method based on V2G. Refer to Figure 1Flow schematic diagram of the V2G-based energy scheduling method shown. Specifically, the V2G-based energy scheduling method includes steps S1 to S3:

[0029] S1. Construct an optimal carbon emission reduction objective function and a minimum cost objective function.

[0030] The optimal carbon emission reduction objective function and the minimum cost objective function are as follows:

[0031] ;

[0032] ;

[0033] Among them, is the total carbon emissions of a plug-in hybrid vehicle in the V2G energy scheduling scenario, where the subscript is the absolute value of the electricity exchanged between the plug-in hybrid vehicle and the power grid in time period , the subscript is the fuel consumption in time period , the subscript is a variable reflecting the vehicle mode, and the vehicle modes include vehicle charging mode (G2V), electric power transmission mode (using V2G), and fuel transmission mode (using oil V2G). The vehicle charging mode means that the power grid charges the plug-in hybrid vehicle. The electric power transmission mode means that the electric power of the plug-in hybrid vehicle is transmitted to the power grid. The fuel transmission mode means that the fuel of the plug-in hybrid vehicle is transmitted to the power grid. The subscript is the proportion of the fuel consumed for the return journey at the last moment to the remaining fuel, and the subscript is the proportion of the electric energy consumed for the return journey at the last moment to the remaining electric energy. The remaining fuel refers to the fuel remaining after the plug-in hybrid vehicle completes V2G, and the remaining electric energy refers to the electric energy remaining after the plug-in hybrid vehicle completes V2G; is the carbon emissions of the fuel consumed during the return journey; is the carbon emissions of the electric energy consumed during the return journey; is the carbon emissions of the fuel consumed by the plug-in hybrid vehicle in time period ; is the carbon emissions generated when the plug-in hybrid vehicle participates in V2G and transmits electric power back to the power grid in time period ; is time period , is the total number of time periods for the plug-in hybrid vehicle to perform energy scheduling 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 journey, is a time period the cost of the fuel consumed by the plug-in hybrid vehicle is a time period the cost consumed by the plug-in hybrid vehicle for the power exchange with the power grid through the charging pile; the return process is the process of the plug-in hybrid vehicle driving back from the charging pile to the owner's residence after completing V2G.

[0034] S2. Solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain the optimal energy scheduling strategy.

[0035] S3. Control the plug-in hybrid 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 vehicle using the fuel and / or the electric energy to send power to the power grid.

[0036] It should be noted that the application scenario of the method is the vehicle-to-grid (V2G) scenario. V2G technology refers to the technology of vehicles sending power to the power grid, and its core idea is to use the energy storage of a large number of vehicles as a buffer for the power grid. By using V2G technology, the problems of low power grid efficiency and large power grid load fluctuations can not only be greatly alleviated, but also benefits can be created for vehicle owners.

[0037] 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, considering the carbon emissions in the V2G mode. In the V2G energy scheduling scenario, the main carbon emissions include: 1. The carbon emissions caused by using fuel to power the plug-in hybrid vehicle during the process of the plug-in hybrid vehicle driving back from the charging pile to the owner's residence after completing V2G; 2. The carbon emissions caused by using electric energy to power the plug-in hybrid vehicle during the process of driving back from the charging pile to the owner's residence after completing V2G; 3. The carbon emissions generated by the plug-in hybrid vehicle using fuel to send power to the power grid in the V2G mode; 4. The carbon emissions generated by the plug-in hybrid vehicle sending electric energy 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 the fuel consumed by the plug-in hybrid vehicle during the process of driving back from the charging pile to the owner's residence after completing V2G; 2. For the fuel consumed by the plug-in hybrid vehicle to send power to the power grid at the charging pile, its cost is the cost after considering the revenue generated by fuel power transmission; 3. The cost generated by the exchange of electric energy between the plug-in hybrid vehicle and the power grid at the charging pile.

[0038] Specifically, in step S2, the multi-objective function is solved to find, as much as possible, an energy scheduling strategy with low carbon emissions and low cost, so that the optimal energy scheduling strategy found can limit both the carbon emissions and the cost within an acceptable range, avoiding excessive carbon emissions or excessive costs.

[0039] Specifically, in step S3, the optimal energy scheduling strategy is actually a control strategy for a plug-in hybrid vehicle to deliver electricity to the power grid using fuel or electricity in the V2G mode, and the energy scheduling is controlled according to this strategy.

[0040] Compared with the prior art, the method disclosed in the embodiments of the present invention first constructs an optimal carbon emission reduction objective function and a minimum cost objective function by considering factors such as the carbon emissions of the fuel consumed during the return journey of the plug-in hybrid vehicle, the carbon emissions of the electric energy consumed during the return journey, the carbon emissions of the fuel consumed when the plug-in hybrid vehicle conducts energy scheduling with the power grid, the carbon emissions generated when the plug-in hybrid vehicle sends electric energy back to the power grid during energy scheduling with the power grid, the cost of the fuel consumed during the return journey, and the cost consumed when the plug-in hybrid vehicle exchanges electric energy with the power grid in the V2G energy scheduling scenario; then, the multi-objective function is solved to obtain the optimal energy scheduling strategy; finally, the plug-in hybrid vehicle is controlled to use fuel and electric energy according to the obtained optimal energy scheduling strategy to conduct V2G energy scheduling with the power grid, effectively reducing the carbon emissions of energy scheduling in the V2G mode and being beneficial to environmental protection.

[0041] In a preferred embodiment, based on steps S1 to S3, the following formulas are further set:

[0042] ;

[0043] ;

[0044] ;

[0045] ;

[0046] Among them, represents the fuel consumption during the return journey, represents the unit carbon emission of the fuel; represents the electric energy consumption during the return journey, represents the unit carbon emission of the electric energy; represents the fuel power transmission state, and when using the fuel to transmit power to the power grid the value of is 1, and when not using the fuel to transmit power to the power grid The value is 0; Indicates a time period The amount of fuel consumed; Indicates the power transmission state of electric energy. When using the electric energy of the plug-in hybrid vehicle to transmit power to the power grid The value is 1. When not using the electric energy of the plug-in hybrid vehicle to transmit power to the power grid The value is 0, Is the plug-in hybrid vehicle in the time period The absolute value of the amount of electricity exchanged with the power grid.

[0047] Specifically, in this embodiment, by multiplying the amount of fuel consumed by the plug-in hybrid vehicle during the return journey by the unit carbon emission when the fuel is used, the carbon emission of the fuel consumed during the return journey is obtained. By multiplying the amount of electric energy consumed by the plug-in hybrid vehicle during the return journey by the unit carbon emission of the electric energy, the carbon emission of the fuel consumed during the return journey is obtained. By multiplying the amount of fuel consumed by the plug-in hybrid vehicle using fuel to transmit power to the power grid by the unit carbon emission when the fuel is used, the carbon emission corresponding to the method of using fuel to transmit power to the power grid is obtained.

[0048] Further, the fuel is a mixed fuel, and the mixed fuel is composed of e-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 for producing the e-fuel in each unit of the mixed fuel.

[0049] Specifically, the plug-in hybrid vehicle is powered by a mixed fuel and electric energy. The plug-in hybrid vehicle can use the mixed fuel and electric energy to transmit power to the power grid. The mixed fuel includes e-fuel and traditional fuel. The traditional fuel is gasoline, and the e-fuel is E-fuel, also known as synthetic fuel. E-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. E-fuel is a liquid hydrocarbon chain fuel generated by catalytic reaction of hydrogen generated by electrolysis of water with carbon dioxide. In the process of generating e-fuel, in order to reduce emission indicators, the hydrogen is obtained by the method of "electrolyzing water", and the carbon dioxide is directly collected from industrial waste gas or ordinary air. Thus, the carbon emissions generated by e-fuel are mainly the carbon emissions generated for producing e-fuel. Therefore, the unit carbon emission of the fuel is the carbon emission generated when the traditional fuel is consumed in each unit of the mixed fuel, plus the carbon emission generated for producing e-fuel.

[0050] Further, the unit carbon emission of the e-fuel is calculated by the following formula:

[0051] ;

[0052] ;

[0053] represents the unit carbon emission of the said e - fuel, represents the unit carbon emission of the green electricity consumed for producing the said e - fuel, represents the electric energy conversion efficiency of the said e - fuel production, represents the carbon emission of the infrastructure required for producing a unit of e - fuel, represents the carbon emission of the carbon capture process required for producing a unit of e - fuel, represents the carbon emission of the synthesis process required for producing a unit of e - fuel, is the total amount of green electricity consumed for generating the said e - fuel, is the total production volume of the said e - fuel;

[0054] In each unit of the said blended fuel, the carbon emission generated for producing the said e - fuel is calculated according to the said set ratio and the unit carbon emission of the e - fuel.

[0055] Specifically, in each unit of the said blended fuel, the carbon emission generated for producing the said e - fuel is obtained by multiplying the proportion of the e - fuel in the blended fuel by the unit carbon emission of the e - fuel. The unit carbon emission of the e - fuel is determined by the carbon emissions generated during the process of generating the e - fuel, and the main influencing factors include the amount of green electricity consumed for generating each unit of e - fuel and the electric energy conversion efficiency during the generation of e - fuel, etc. It should be noted that when the electric energy conversion efficiency increases, the unit carbon emission of the e - fuel will decrease accordingly.

[0056] Furthermore, the calculation formula for the unit carbon emission of the said e - fuel can also be set as:

[0057] ;

[0058] wherein, represents the carbon emission of other processes required for producing a unit of e - fuel, and the specific types of other processes are set according to the actual situation and are not limited herein.

[0059] In a preferred embodiment, on the basis of steps S1 - S3, the method further includes:

[0060] ;

[0061] ;

[0062] ;

[0063] ;

[0064] ;

[0065] wherein, is the unit cost of fuel after subtracting the income obtained by the plug-in hybrid vehicle using the fuel to participate in V2G, is the time period the fuel consumption, is the unit purchase cost of the fuel, is the unit income of the plug-in hybrid vehicle participating in V2G, is the power generation efficiency of the fuel, represents the fuel consumption during the return journey, is the unit cost of electricity after subtracting the income obtained by the plug-in hybrid vehicle using electricity to participate in V2G, is the unit electricity cost when charging the plug-in hybrid vehicle using the charging pile, and the unit electricity cost is a time-of-use price, represents the absolute value of the electricity quantity exchanged between the plug-in hybrid vehicle and the power grid during the time period , and each time period has a corresponding value, represents the fuel power transmission state. When using the fuel to transmit power to the power grid, the value is 1, and when not using the fuel to transmit power to the power grid, the value is 0; represents the vehicle charging state. When the power grid charges the plug-in hybrid vehicle, the value is 1, and when the power grid does not charge the plug-in hybrid vehicle, the value is 0; represents the electricity power transmission state. When using the electricity of the plug-in hybrid vehicle to transmit power to the power grid, the value is 1, and when not using the electricity of the plug-in hybrid vehicle to transmit power to the power grid, the value is 0.

[0066] Specifically, by determining the fuel consumption and the corresponding unit cost in different states, and then calculating the costs in different states, and comparing all the costs, the total cost can be obtained.

[0067] Furthermore, the fuel is a mixed fuel, and the mixed fuel is composed of a traditional fuel and an electronic fuel according to a set ratio; the unit purchase cost of the fuel is calculated by the following formula:

[0068] ;

[0069] ;

[0070] ;

[0071] wherein, is the proportion of the e - fuel in the mixed fuel, is the unit cost of the e - fuel considering the carbon tax, is the unit cost of the traditional fuel considering the carbon tax, is the original unit cost of the e - fuel, is the original unit cost of the traditional fuel, is the cost data of the carbon tax.

[0072] It should be noted that the carbon tax refers to the 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 value of the cost data of the carbon tax, the proportion of the traditional fuel in the mixed fuel, and the proportion of the e - fuel in the mixed fuel are all set according to the actual situation and are not limited here.

[0073] Specifically, when using green electricity to produce E - fuel, the original unit cost of the e - fuel can be determined by the following method:

[0074] Considering the game relationship between the green electricity producer and the E - fuel producer, the supply - demand relationship between the green electricity producer and the E - fuel producer reaches the Nash equilibrium condition:

[0075] ; ;

[0076] 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 the green electricity producer from selling green electricity;

[0077] The calculation formula of

[0078] = ;

[0079] In the formula, is the proportion of renewable energy in the power structure; It is used to represent the relationship between the demand for E-fuel and the green electricity generation, which is a function of the green electricity generation; It is the income obtained by the green electricity producer from selling green electricity; It is used to represent the unit cost of green electricity consumed for the production of E-fuel.

[0080] The relevant cost calculation formula of the E-fuel producer is as follows:

[0081] ;

[0082] ;

[0083] ;

[0084] In the formula, represents the total expenditure cost of the E-fuel producer, is the basic production cost of producing E-fuel, is the electrical energy conversion efficiency of E-fuel production, represents the unit carbon emission of the electronic fuel, represents the unit carbon emission of the green electricity consumed for the production of the electronic fuel, represents the electrical energy conversion efficiency of the electronic fuel production, represents the carbon emission of the infrastructure required for the production of the unit electronic fuel, represents the carbon emission of the carbon capture process required for the production of the unit electronic fuel, represents the carbon emission of the synthesis process required for the production of the unit electronic fuel, represents the carbon emission of other processes required for the production of the unit electronic fuel, is the total green electricity consumption for generating the electronic fuel, is the total production volume of the electronic fuel;

[0085] Set the following formula:

[0086] ;

[0087] ;

[0088] In the formula, is the demand for E-fuel during the is a demand function, and the green electricity generation will affect the demand for E-fuel, is the price at which the E-fuel producer sells E-fuel, that is, the cost for electric vehicle owners to purchase and use E-fuel (i.e., the original unit cost of the electronic fuel).

[0089] By using the above formula, the original unit cost of e-fuel is determined under the condition that the supply-demand relationship between green power producers and e-fuel producers reaches the Nash equilibrium .

[0090] Compared with the prior art, in the energy scheduling method based on V2G provided by the embodiment of the present invention, first, in the V2G energy scheduling scenario, by considering the carbon emissions of the fuel consumed during the return journey of the plug-in hybrid vehicle, the carbon emissions of the electric energy consumed during the return journey, the carbon emissions of the fuel consumed when the plug-in hybrid vehicle performs energy scheduling with the power grid, the carbon emissions generated when the plug-in hybrid vehicle sends the electric energy back to the power grid during energy scheduling with the power grid, the cost of the fuel consumed during the return journey, and the cost consumed when the plug-in hybrid vehicle exchanges electric energy with the power grid and other factors, an optimal carbon emission reduction objective function and a minimum cost objective function are constructed; then, by solving the multi-objective function, an optimal energy scheduling strategy is obtained; finally, by controlling the plug-in hybrid vehicle to perform energy scheduling operations based on the fuel and / or electric energy of the vehicle according to the obtained optimal energy scheduling strategy, the carbon emissions of the energy scheduling between the plug-in hybrid vehicle and the power grid in the V2G mode are effectively reduced, which is beneficial to environmental protection.

[0091] See Figure 2 , Figure 2 which is an energy scheduling device based on V2G provided by the embodiment of the present invention. The energy scheduling device based on V2G includes:

[0092] A function construction module 21 for constructing an optimal carbon emission reduction objective function and a minimum cost objective function:

[0093] ;

[0094] ;

[0095] wherein, is the total carbon emissions of the plug-in hybrid vehicle in the V2G energy scheduling scenario; is the carbon emissions of the fuel consumed during the return journey; is the carbon emissions of the electric energy consumed during the return journey; is the time period the carbon emissions of the fuel consumed by the plug-in hybrid vehicle; is the time period the carbon emissions generated when the plug-in hybrid vehicle participates in V2G and sends the electric energy back to the power grid; is the time period , is the total number of time periods for the plug-in hybrid vehicle to perform energy scheduling 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 journey, is the time period the cost of the fuel consumed by the plug-in hybrid vehicle, is the time period the cost consumed by the plug-in hybrid vehicle for power exchange with the power grid through the charging pile; the return journey is the process of the plug-in hybrid vehicle driving back from the charging pile to the owner's residence after completing V2G;

[0096] A solution module 22, configured to solve the optimal carbon emission reduction objective function and the minimum cost objective function to obtain an optimal energy scheduling strategy;

[0097] An energy scheduling module 23, configured to control the plug-in hybrid 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 vehicle using the fuel and / or the electric energy to supply power to the power grid.

[0098] It should be noted 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 elaborated here.

[0099] 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 during the return journey of the plug-in hybrid vehicle, the carbon emissions of the electric energy consumed during the return journey, the carbon emissions of the fuel consumed when the plug-in hybrid vehicle performs energy scheduling with the power grid, the carbon emissions generated when the plug-in hybrid vehicle sends electric energy back to the power grid during energy scheduling with the power grid, the cost of the fuel consumed during the return journey, and the cost consumed when the plug-in hybrid vehicle exchanges electric energy with the power grid, etc., to construct the optimal carbon emission reduction objective function and the minimum cost objective function; then, by solving the multi-objective function to obtain the optimal energy scheduling strategy; finally, by controlling the plug-in hybrid vehicle to perform energy scheduling operations based on the fuel and / or electric energy of the vehicle according to the obtained optimal energy scheduling strategy, effectively reducing the carbon emissions of energy scheduling between the plug-in hybrid vehicle and the power grid in the V2G mode, which is beneficial to environmental protection.

[0100] See Figure 3, embodiments of the present invention further provide an energy scheduling device based on V2G, 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 in the embodiments of the above-mentioned V2G-based energy scheduling method, such as Figure 1 S1 to S3 in; or, when the processor 31 executes the computer program, it implements the functions of each module in the above-mentioned device embodiments.

[0101] Exemplarily, the computer program can be divided into one or more modules. 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 can be a series of computer program instruction segments capable of performing specific functions, and this instruction segment is used to describe the execution process of the computer program in the V2G-based energy scheduling device. For example, the computer program can be divided into multiple modules, and each module is used to execute the specific steps in the method described in any of the above embodiments.

[0102] The V2G-based energy scheduling device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. 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 can understand that the V2G-based energy scheduling device may further include input / output devices, network access devices, buses, etc.

[0103] The processor 31 may be a central processing unit (CPU), or may also be 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 may be a microprocessor or the processor may also be any conventional processor, etc. The processor 31 is the control center of the V2G-based energy scheduling device, and uses various interfaces and lines to connect various parts of the entire V2G-based energy scheduling device.

[0104] The memory 32 can be used to store the computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory 32, and invoking the data stored in the memory 32, the processor 31 realizes various functions of the V2G-based energy scheduling device. The memory 32 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as an image playback function, 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 high-speed random access memory, and can also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0105] Among them, if the modules integrated in the V2G-based energy scheduling device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. 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 realized. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. 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 mobile hard disk, a magnetic disk, an optical disc, 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.

[0106] The embodiment of the present invention also provides a computer program product, including a computer program / instructions, and when the computer program / instructions are executed by a processor, the V2G-based energy scheduling method as described in any of the above embodiments is realized.

[0107] The above is the preferred implementation manner of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope 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 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.

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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