Charging and discharging scheduling method, device and equipment of electric vehicle, storage medium and program product

Abstract

The invention relates to the technical field of electric power, provides a charging and discharging scheduling method, device and equipment for an electric vehicle, a storage medium and a program product, and can reduce the carbon emission of a micro-grid in a vehicle-network interaction scene, maintain the stability of the micro-grid and increase the resource benefits of the electric vehicle when the charging and discharging of the electric vehicle are scheduled. According to the method, a scheduling scheme of the electric vehicle is obtained based on a first objective function with minimization of the power fluctuation ratio of the micro-grid as a target, a second objective function with minimization of the carbon emission of the micro-grid as a target and a third objective function with maximization of the resource inflow of the electric vehicle as a target; and according to the scheduling scheme, scheduling charging and discharging of the electric vehicle.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a method, device, computer equipment, storage medium and computer program product for scheduling charging and discharging of electric vehicles. Background Art

[0002] With the proposal of the "dual carbon" goal, methods to reduce carbon emissions from microgrids have been further studied. Among them, electric vehicles have low carbon emissions and are environmentally friendly and energy-saving, and have been widely developed. The charging behavior of electric vehicle owners is highly random. If the market share of electric vehicles is not very high, this random charging behavior will not have much impact on the operation of microgrids. With the rapid increase in the number of electric vehicles, their large-scale disorderly access to microgrids for charging will lead to a sharp increase in grid load, which will in turn affect the stability and economy of the power system. Therefore, tapping the mobile energy storage characteristics of electric vehicles and realizing their orderly interaction with the power grid has become an important development direction of vehicle-grid interaction technology. The core of V2G (Vehicle-to-Grid) technology is to manage the charging and discharging process of electric vehicles through two-way communication and energy flow, thereby minimizing the impact on the power grid and improving the flexibility and stability of the power grid.

[0003] Traditional electric vehicle scheduling based on vehicle-grid interaction scenarios is generally based on integrated energy systems, such as wind power, photovoltaics, energy storage and other energy sources. There is no separate scheduling for the charging and discharging of electric vehicles, and there is no comprehensive consideration of multiple indicators such as microgrid stability, environmental protection and resource efficiency. Summary of the invention

[0004] Based on this, it is necessary to provide a charging and discharging scheduling method, device, computer equipment, storage medium and computer program product for electric vehicles in response to the above technical problems.

[0005] The present application provides a charging and discharging scheduling method for an electric vehicle, the method comprising:

[0006] Based on the power variation of the microgrid at adjacent moments within the statistical time interval, a first objective function with the goal of minimizing the power fluctuation rate of the microgrid is obtained;

[0007] Based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the carbon emissions of each electric vehicle during charging and discharging at a single moment, a second objective function with the goal of minimizing the carbon emissions of the microgrid is obtained;

[0008] Based on the expression of the resource inflow obtained from selling electricity at a single moment of the electric vehicle, the expression of the resource cost generated by charging at a single moment, and the expression of the resource loss at a single moment, a third objective function aiming at maximizing the resource inflow of the electric vehicle is obtained;

[0009] Based on the first objective function, the second objective function, and the third objective function, a scheduling scheme for the electric vehicle is obtained;

[0010] According to the scheduling scheme, the charging and discharging of the electric vehicle are scheduled.

[0011] In one embodiment, the method further includes:

[0012] Obtain the charging and discharging mathematical model of the electric vehicle;

[0013] According to the charging and discharging mathematical model, obtain the expression of the state of charge of the electric vehicle battery at a single moment;

[0014] According to the expression of the state of charge of the battery, obtain the expression of the resource loss.

[0015] In one embodiment, based on the expression of the resource inflow obtained from selling electricity at a single moment of the electric vehicle, the expression of the resource cost generated by charging at a single moment, and the expression of the resource loss at a single moment, obtaining a third objective function aiming at maximizing the resource inflow of the electric vehicle includes:

[0016] Subtract the expression of the resource cost generated by charging at a single moment and the expression of the resource loss at a single moment from the expression of the resource inflow obtained from selling electricity at a single moment of the electric vehicle to obtain a third objective function aiming at maximizing the resource inflow of the electric vehicle.

[0017] In one embodiment, based on the first objective function, the second objective function, and the third objective function, obtaining a scheduling scheme for the electric vehicle includes:

[0018] Taking the charging power of the electric vehicle battery at a single moment not being greater than the maximum charging power, the discharging power of the electric vehicle at a single moment not being greater than the maximum discharging power, and the state of charge of the electric vehicle battery at a single moment being within the upper and lower limit intervals as constraint conditions, and solving the first objective function, the second objective function, and the third objective function;

[0019] According to the solution result, obtain the scheduling scheme of the electric vehicle.

[0020] In one embodiment, based on the number of electric vehicles scheduled by the microgrid within a statistical time interval and the carbon emissions of charging and discharging of each electric vehicle at a single moment, a second objective function aiming at minimizing the carbon emissions of the microgrid is obtained, including:

[0021] Based on the power generation amount and carbon emission factor of the microgrid within a statistical time interval, a carbon emission expression related to the power generation of the microgrid is obtained;

[0022] Based on the number of electric vehicles scheduled by the microgrid within a statistical time interval and the carbon emissions of charging and discharging of each electric vehicle at a single moment, a carbon emission expression related to the charging and discharging of electric vehicles is obtained;

[0023] Based on the carbon emission expression related to the power generation of the microgrid plus the carbon emission expression related to the charging and discharging of electric vehicles, a second objective function aiming at minimizing the carbon emissions of the microgrid is obtained.

[0024] In one embodiment, based on the carbon emission expression related to the power generation of the microgrid plus the carbon emission expression related to the charging and discharging of electric vehicles, a second objective function aiming at minimizing the carbon emissions of the microgrid is obtained, including:

[0025] Based on the carbon emission expression related to the power generation of the microgrid minus the initial carbon quota of the microgrid and plus the carbon emission expression related to the charging and discharging of electric vehicles, a second objective function aiming at minimizing the carbon emissions of the microgrid is obtained.

[0026] The present application provides a charging and discharging scheduling device for electric vehicles, and the device includes:

[0027] A first objective function acquisition module, configured to obtain a first objective function aiming at minimizing the power fluctuation rate of the microgrid based on the power change situation of the microgrid at adjacent moments within a statistical time interval;

[0028] A second objective function module, configured to obtain a second objective function aiming at minimizing the carbon emissions of the microgrid based on the number of electric vehicles scheduled by the microgrid within a statistical time interval and the carbon emissions of charging and discharging of each electric vehicle at a single moment;

[0029] A third objective function module, configured to obtain a third objective function aiming at maximizing the resource inflow of the electric vehicle based on the expression of the resource inflow amount obtained from selling electricity of the electric vehicle at a single moment, the expression of the resource expenditure amount generated by charging at a single moment, and the expression of the resource loss amount at a single moment;

[0030] A scheduling scheme acquisition module, configured to obtain a scheduling scheme for an electric vehicle based on the first objective function, the second objective function, and the third objective function;

[0031] A scheduling processing module, configured to schedule the charging and discharging of the electric vehicle according to the scheduling scheme.

[0032] This application provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor executes the above method.

[0033] This application provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to implement the above method.

[0034] This application provides a computer program product, on which a computer program is stored, and the computer program is executed by a processor to implement the above method.

[0035] For the above-mentioned electric vehicle charging and discharging scheduling method, device, computer device, storage medium, and computer program product, based on the power change situation of the microgrid at adjacent moments within a statistical time interval, a first objective function aiming to minimize the power volatility of the microgrid is obtained; based on the number of electric vehicles scheduled by the microgrid within a statistical time interval and the charging and discharging carbon emissions of each electric vehicle at a single moment, a second objective function aiming to minimize the carbon emissions of the microgrid is obtained; based on the expression of the resource inflow obtained from selling electricity by the electric vehicle at a single moment, the expression of the resource cost generated by charging at a single moment, and the expression of the resource loss at a single moment, a third objective function aiming to maximize the resource inflow of the electric vehicle is obtained; based on the first objective function, the second objective function, and the third objective function, a scheduling scheme for the electric vehicle is obtained; and according to the scheduling scheme, the charging and discharging of the electric vehicle are scheduled. When scheduling the charging and discharging of the electric vehicle, the solution provided by this application fully considers indicators such as the stability, environmental friendliness, and resource efficiency of the microgrid. It can not only effectively guide the orderly charging and discharging of electric vehicles, that is, the electric vehicle acts as a power source to supply power to the microgrid during peak electricity consumption periods and acts as a load to absorb electric energy from the microgrid during low electricity consumption periods, realizing a reasonable interaction between the electric vehicle and the power grid, enhancing the flexibility of vehicle-grid interaction, and improving the application value of electric vehicles, but also reducing the carbon emissions of the microgrid in the vehicle-grid interaction scenario, maintaining the stability of the microgrid, and increasing the resource efficiency of electric vehicles. Description of the Drawings

[0036] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the accompanying drawings required for the description of the embodiments or related technologies. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0037] Figure 1 It is a schematic flowchart of the charging and discharging scheduling method for an electric vehicle in an embodiment;

[0038] Figure 2 It is a schematic flowchart of the process for obtaining the expression of the resource loss amount in an embodiment;

[0039] Figure 3 It is a schematic flowchart of the solution process in an embodiment;

[0040] Figure 4 It is a structural block diagram of the charging and discharging scheduling device for an electric vehicle in an embodiment;

[0041] Figure 5 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0042] In order to make the objectives, technical solutions, and advantages of the present application clearer, the following further details the present application in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] The charging and discharging scheduling method for an electric vehicle provided by the present application can be executed by a computer device and includes Figure 1 The steps shown.

[0044] Step S101: Based on the power change situation of the microgrid at adjacent moments within the statistical time interval, obtain a first objective function with the minimization of the power volatility of the microgrid as the target.

[0045] The stability of the microgrid can be characterized by the index of the power volatility of the microgrid; the smaller the power volatility of the microgrid, the more stable the microgrid; the larger the power volatility of the microgrid, the less stable the microgrid.

[0046] The power volatility of the microgrid can be reflected by the power change situation of the microgrid at adjacent moments within the statistical time interval; the greater the power change of the microgrid at adjacent moments within the statistical time interval, the greater the power volatility; the smaller the power change of the microgrid at adjacent moments within the statistical time interval, the smaller the power volatility.

[0047] The mathematical expression of the first objective function obtained in this step can be:

[0048] ;

[0049] where, is the power of the microgrid at time t, and T is the statistical time interval (which can also be called the scheduling period).

[0050] Step S102: Based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the carbon emissions of each electric vehicle during charging and discharging at a single moment, obtain a second objective function with the goal of minimizing the carbon emissions of the microgrid.

[0051] The environmental friendliness of the microgrid can be characterized by the indicator of the carbon emissions of the microgrid; the less carbon emissions the microgrid has, the more environmentally friendly the microgrid is; the more carbon emissions the microgrid has, the less environmentally friendly the microgrid is.

[0052] The carbon emissions of the microgrid are related to the number of battery vehicles dispatched by the microgrid within the statistical time interval, and the carbon emissions of the microgrid are also related to the carbon emissions of each electric vehicle during charging and discharging at a single moment. Therefore, in this step, based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the carbon emissions of each electric vehicle during charging and discharging at a single moment, a second objective function with the goal of minimizing the carbon emissions of the microgrid is obtained.

[0053] Step S103: Based on the expression of the resource inflow obtained from selling electricity by the electric vehicle at a single moment, the expression of the resource cost generated by charging at a single moment, and the expression of the resource loss at a single moment, obtain a third objective function with the goal of maximizing the resource inflow of the electric vehicle.

[0054] Taking a single moment as the t-th moment as an example, for the i-th electric vehicle, the expression of the resource inflow obtained from selling electricity by the i-th electric vehicle at the t-th moment is denoted as ; the expression of the resource cost generated by charging by the i-th electric vehicle at the t-th moment is denoted as ; the expression of the resource loss of the i-th electric vehicle at the t-th moment is denoted as .

[0055] According to the expression of the resource inflow obtained from selling electricity by the i-th electric vehicle at the t-th moment , the expression of the resource cost generated by charging by the i-th electric vehicle at the t-th moment , the expression of the resource loss of the i-th electric vehicle at the t-th moment , the third objective function aiming to maximize the resource inflow of the electric vehicle can be obtained.

[0056] Step S104: Based on the first objective function, the second objective function, and the third objective function, obtain the scheduling scheme of the electric vehicle.

[0057] After obtaining the first objective function, the second objective function, and the third objective function, they can be solved to obtain the scheduling scheme of the electric vehicle.

[0058] Specifically, the improved moth-flame multi-objective optimization algorithm based on R domination or multi-objective particle swarm optimization can be used for solving to obtain the scheduling scheme of the electric vehicle. The scheduling scheme of the electric vehicle includes the charge and discharge states and durations of each electric vehicle scheduled by the microgrid within the statistical time interval.

[0059] Step S105: Schedule the charge and discharge of the electric vehicle according to the scheduling scheme.

[0060] The scheduling scheme of the electric vehicle includes the charge and discharge states and durations of each electric vehicle scheduled by the microgrid within the statistical time interval. Therefore, the charge and discharge states and durations of each electric vehicle can be sent to the corresponding vehicle owner to remind the vehicle owner to charge and discharge according to the corresponding charge and discharge states and durations, so as to complete the scheduling of the charge and discharge of the electric vehicle.

[0061] In the above charging and discharging scheduling method for electric vehicles, based on the power change of the microgrid at adjacent moments within a statistical time interval, a first objective function aiming to minimize the power volatility of the microgrid is obtained; based on the number of electric vehicles scheduled by the microgrid within a statistical time interval and the carbon emissions of each electric vehicle during charging and discharging at a single moment, a second objective function aiming to minimize the carbon emissions of the microgrid is obtained; based on the expressions of the resource inflow of the electric vehicle due to power selling at a single moment, the resource cost due to charging at a single moment, and the resource loss at a single moment, a third objective function aiming to maximize the resource inflow of the electric vehicle is obtained; based on the first objective function, the second objective function, and the third objective function, a scheduling plan for the electric vehicle is obtained; according to the scheduling plan, the charging and discharging of the electric vehicle are scheduled. When scheduling the charging and discharging of the electric vehicle, the solution provided in this application fully considers indicators such as the stability, environmental friendliness, and resource efficiency of the microgrid. It can not only effectively guide the orderly charging and discharging of electric vehicles, that is, the electric vehicle acts as a power source to supply power to the microgrid during the peak electricity consumption period and acts as a load to absorb electric energy from the microgrid during the low electricity consumption period, realizing a reasonable interaction between the electric vehicle and the grid, enhancing the flexibility of vehicle-grid interaction, improving the application value of the electric vehicle, but also reducing the carbon emissions of the microgrid in the vehicle-grid interaction scenario, maintaining the stability of the microgrid, and increasing the resource efficiency of the electric vehicle.

[0062] In one embodiment, the method provided in this application further includes Figure 2 the steps shown:

[0063] Step S201, obtaining the charging and discharging mathematical model of the electric vehicle; Step S202, obtaining the state-of-charge expression of the electric vehicle at a single moment according to the charging and discharging mathematical model; Step S203, obtaining the expression of the resource loss according to the state-of-charge expression.

[0064] Taking the i-th electric vehicle at time t as an example for introduction:

[0065] The charging and discharging process of the battery of the electric vehicle can be described by the following equation:

[0066] ;

[0067] where is the state-of-charge of the i-th electric vehicle at time t, is the state-of-charge of the i-th electric vehicle at time t - 1, is the charging power of the i-th electric vehicle at time t, is the discharging power of the i-th electric vehicle at time t, is the total capacity of the battery of the i-th electric vehicle, is the time step. is 0 or 1, which is a variable representing the charging and discharging state of the battery of the i-th electric vehicle; when is 1, it means the i-th electric vehicle is charging; when is 0, it means the i-th electric vehicle is discharging. is 0 or 1, which is a variable representing the charging and discharging state of the battery of the i-th electric vehicle; when is 1, it means the i-th electric vehicle is discharging; when is 0, it means the i-th electric vehicle is charging.

[0068] ;

[0069] ;

[0070] Among them, is the charging and discharging power of the battery of the i-th electric vehicle, is the charging efficiency of the battery of the i-th electric vehicle, is the discharging efficiency of the battery of the i-th electric vehicle.

[0071] can take , as the expression of the state of charge of the battery of the i-th electric vehicle at time t.

[0072] According to the expression of the state of charge of the battery of the i-th electric vehicle at time t, the expression of the resource loss amount can be obtained; the expression of the resource loss amount can be: .

[0073] is the resource loss amount of the battery of the i-th electric vehicle at time t; is the value of the electric vehicle battery; is the time required to fully charge the battery of the i-th electric vehicle; is the maximum number of charge and discharge cycles of the battery of the i-th electric vehicle.

[0074] Based on the expression of the state of charge of the battery obtained from the charging and discharging mathematical model of the electric vehicle in this embodiment, it can accurately reflect the state of charge of the battery at a single moment; based on the expression of the resource loss amount, the resource loss situation of the battery under different charging and discharging conditions, such as battery aging loss, etc., can be analyzed, so as to obtain a more reasonable charging and discharging scheduling scheme for the electric vehicle.

[0075] In one embodiment, based on the expression of the resource inflow amount obtained from selling electricity at a single moment of the electric vehicle, the expression of the resource cost amount generated by charging at a single moment, and the expression of the resource loss amount at a single moment, a third objective function with the maximization of the resource inflow amount of the electric vehicle as the goal is obtained, including:

[0076] Subtract the expression of the resource inflow obtained from selling electricity by the electric vehicle at a single moment from the expression of the resource cost generated by charging at a single moment and the expression of the resource loss at a single moment, to obtain a third objective function aiming at maximizing the resource inflow of the electric vehicle.

[0077] Taking a single moment as the t-th moment as an example, for the i-th electric vehicle, let the expression of the resource inflow obtained from selling electricity by the i-th electric vehicle at the t-th moment be denoted as ; let the expression of the resource cost generated by charging by the i-th electric vehicle at the t-th moment be denoted as ; let the expression of the resource loss of the i-th electric vehicle at the t-th moment be denoted as .

[0078] Among them, the expression of the resource inflow obtained from selling electricity by the i-th electric vehicle at the t-th moment is: ; is the resource inflow obtained from selling electricity by the i-th electric vehicle at the t-th moment, is the electricity selling price of the i-th electric vehicle at the t-th moment, is the discharging power of the i-th electric vehicle at the t-th moment.

[0079] The expression of the resource cost generated by charging by the i-th electric vehicle at the t-th moment is: ; is the resource cost generated by charging by the i-th electric vehicle at the t-th moment; is the charging price of the i-th electric vehicle at the t-th moment; is the charging power of the i-th electric vehicle at the t-th moment.

[0080] The third objective function aiming at maximizing the resource inflow of the electric vehicle can be:

[0081] .

[0082] I represents the number of electric vehicles dispatched by the microgrid within the statistical time interval.

[0083] The third objective function of this embodiment aiming at maximizing the resource inflow of the electric vehicle can guide the orderly charging and discharging of electric vehicles, increase power supply during the peak load of the microgrid, reduce power demand during the low load, play a role in peak shaving and valley filling, help smooth the load curve of the microgrid, reduce the peak-valley difference of the microgrid, and improve the stability and reliability of the microgrid.

[0084] In one embodiment, based on the first objective function, the second objective function and the third objective function, a dispatching scheme for electric vehicles is obtained, includingFigure 3 Steps shown:

[0085] Step S301: Solve the first objective function, the second objective function, and the third objective function under the constraints that the charging power of the electric vehicle battery at a single moment is not greater than the maximum charging power, the discharging power of the electric vehicle at a single moment is not greater than the maximum discharging power, and the state of charge of the electric vehicle battery at a single moment is within the upper and lower limit intervals; Step S302: Obtain the scheduling scheme of the electric vehicle according to the solution result.

[0086] The constraint conditions established in this embodiment can be written as:

[0087] ;

[0088] ;

[0089] ;

[0090] ;

[0091] where, represents the maximum charging power of the battery of the i-th electric vehicle, represents the maximum discharging power of the battery of the i-th electric vehicle, represents the lower limit value of the state of charge of the battery of the i-th electric vehicle, represents the upper limit value of the state of charge of the battery of the i-th electric vehicle. is 0 or 1, belonging to a variable, representing the charging and discharging state of the battery of the i-th electric vehicle; when is 1, it means the i-th electric vehicle is charging; when is 0, it means the i-th electric vehicle is discharging. is 0 or 1, belonging to a variable, representing the charging and discharging state of the battery of the i-th electric vehicle; when is 1, it means the i-th electric vehicle is discharging; when is 0, it means the i-th electric vehicle is charging.

[0092] The microgrid satisfies power balance, specifically as follows:

[0093] ;

[0094] ;

[0095] where, is the power generation of the thermal power unit in the microgrid at time t, is the charging and discharging power of the electric vehicle at time t, is the power loss of the microgrid at time t, $P_{load}(t)$ is the load power of the microgrid at time $t$, and $I$ represents the number of electric vehicles dispatched by the microgrid within the statistical time interval. $P_{i}(t)$ is the charging and discharging power of the $i$-th electric vehicle at time $t$.

[0096] In one embodiment, based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the charging and discharging carbon emissions of each electric vehicle at a single moment, a second objective function aiming at minimizing the carbon emissions of the microgrid is obtained, including:

[0097] Based on the power generation and carbon emission factor of the microgrid within the statistical time interval, an expression for carbon emissions related to the power generation of the microgrid is obtained; based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the charging and discharging carbon emissions of each electric vehicle at a single moment, an expression for carbon emissions related to the charging and discharging of electric vehicles is obtained; based on adding the expression for carbon emissions related to the power generation of the microgrid and the expression for carbon emissions related to the charging and discharging of electric vehicles, a second objective function aiming at minimizing the carbon emissions of the microgrid is obtained.

[0098] Based on the power generation and carbon emission factor of the microgrid within the statistical time interval, an expression for carbon emissions related to the power generation of the microgrid is obtained; the expression for carbon emissions related to the power generation of the microgrid can be written as ; where $P_{th}(t)$ is the power generation of the thermal power unit of the microgrid at time $t$, $\lambda_{th}$ is the carbon emission factor per unit power of thermal power.

[0099] Based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the charging and discharging carbon emissions of each electric vehicle at a single moment, an expression for carbon emissions related to the charging and discharging of electric vehicles is obtained; the expression for carbon emissions related to the charging and discharging of electric vehicles can be written as ; where $e_{i}(t)$ is the charging and discharging carbon emissions of the $i$-th electric vehicle at time $t$; $I$ is the number of electric vehicles dispatched by the microgrid within the statistical time interval.

[0100] Furthermore, by combining the expression for carbon emissions related to the power generation of the microgrid and the expression for carbon emissions related to the charging and discharging of electric vehicles, a second objective function aiming at minimizing the carbon emissions of the microgrid can be obtained.

[0101] In one embodiment, based on adding the expression for carbon emissions related to the power generation of the microgrid and the expression for carbon emissions related to the charging and discharging of electric vehicles, a second objective function aiming at minimizing the carbon emissions of the microgrid is obtained, including:

[0102] Subtract the initial carbon quota of the microgrid from the carbon emission expression related to the power generation of the microgrid, and add the carbon emission expression related to the charging and discharging of electric vehicles to obtain the second objective function aiming at minimizing the carbon emissions of the microgrid.

[0103] The second objective function obtained in this embodiment aims at minimizing the carbon emissions of the microgrid, which can ensure the environmental protection of the microgrid.

[0104] The second objective function can be written as:

[0105] ;

[0106] Where, is the power generation of the thermal power unit of the microgrid at time t, is the carbon emission factor per unit of thermal power, is the initial carbon quota of the microgrid, is the carbon emission of the i-th electric vehicle during charging and discharging at time t; is the number of electric vehicles dispatched by the microgrid within the statistical time interval.

[0107] When the i-th electric vehicle discharges, its carbon emission is:

[0108] ;

[0109] When the i-th electric vehicle charges, its carbon emission is:

[0110] ;

[0111] Where, is the carbon emission factor per unit of the electric vehicle battery, is the charging and discharging power of the i-th electric vehicle battery at time t.

[0112] To better understand the above method, the following details an application example of the charging and discharging scheduling method of the electric vehicle in this application.

[0113] Step 1: Establish a mathematical model for the charging and discharging of electric vehicles.

[0114] Taking the i-th electric vehicle at time t as an example for introduction:

[0115] The charging and discharging process of the battery of the electric vehicle can be described by the following equation:

[0116] ;

[0117] Where, is the state of charge of the battery of the i-th electric vehicle at time t, is the state of charge of the battery of the \(i\)-th electric vehicle at time \(t - 1\), is the charging power of the \(i\)-th electric vehicle at time \(t\), is the discharging power of the \(i\)-th electric vehicle at time \(t\), is the total battery capacity of the \(i\)-th electric vehicle, is the time step. is 0 or 1, which is a variable representing the charging and discharging state of the battery of the \(i\)-th electric vehicle; when is 1, it means the \(i\)-th electric vehicle is charging; when is 0, it means the \(i\)-th electric vehicle is discharging. is 0 or 1, which is a variable representing the charging and discharging state of the battery of the \(i\)-th electric vehicle; when is 1, it means the \(i\)-th electric vehicle is discharging; when is 0, it means the \(i\)-th electric vehicle is charging.

[0118] ;

[0119] ;

[0120] Among them, is the charging and discharging power of the battery of the \(i\)-th electric vehicle, is the charging efficiency of the battery of the \(i\)-th electric vehicle, is the discharging efficiency of the battery of the \(i\)-th electric vehicle.

[0121] Step 2: Establish an objective function with multiple indicators for the microgrid containing electric vehicles, including three indicators: the power volatility of the microgrid, the carbon emissions of the microgrid, and the resource benefit of the electric vehicle.

[0122] (1) The mathematical expression of the first objective function aiming at minimizing the power volatility of the microgrid can be:

[0123] ;

[0124] Among them, is the power of the microgrid at time \(t\), and \(T\) is the statistical time interval (which can also be called the scheduling period).

[0125] (2) The mathematical expression of the second objective function aiming at minimizing the carbon emissions of the microgrid can be:

[0126] ;

[0127] Among them, is the power generation of the thermal power unit of the microgrid at time \(t\), is the carbon emission factor per unit power of thermal power, is the initial carbon quota of the microgrid, is the carbon emission of the i-th electric vehicle during charging and discharging at time t; is the number of electric vehicles dispatched by the microgrid within the statistical time interval.

[0128] When the i-th electric vehicle discharges, its carbon emission is:

[0129] ;

[0130] When the i-th electric vehicle charges, its carbon emission is:

[0131] ;

[0132] Among them, is the carbon emission factor per unit of electric energy of the electric vehicle battery, is the charging and discharging power of the i-th electric vehicle battery at time t.

[0133] (3) The mathematical expression of the third objective function aiming at maximizing the resource inflow of electric vehicles can be:

[0134] ;

[0135] Among them, ;

[0136] ;

[0137] ;

[0138] is the resource inflow obtained by the i-th electric vehicle from selling electricity at time t, is the selling price of the i-th electric vehicle at time t, is the discharging power of the i-th electric vehicle at time t.

[0139] is the resource cost generated by the i-th electric vehicle from charging at time t; is the charging price of the i-th electric vehicle at time t; is the charging power of the i-th electric vehicle at time t.

[0140] is the resource loss of the i-th electric vehicle battery at time t; is the value of the electric vehicle battery; is the time required for the i-th electric vehicle battery to be fully charged; is the maximum number of charge and discharge cycles of the i-th electric vehicle battery.

[0141] Step 3. Establish the constraint conditions of the objective function. The constraint conditions include:

[0142] ;

[0143] ;

[0144] ;

[0145] ;

[0146] where, represents the maximum charging power of the battery of the i-th electric vehicle, represents the maximum discharging power of the battery of the i-th electric vehicle, represents the lower limit of the state of charge of the battery of the i-th electric vehicle, represents the upper limit of the state of charge of the battery of the i-th electric vehicle. is 0 or 1, which is a variable representing the charging and discharging state of the battery of the i-th electric vehicle; when is 1, it means the i-th electric vehicle is charging; when is 0, it means the i-th electric vehicle is discharging. is 0 or 1, which is a variable representing the charging and discharging state of the battery of the i-th electric vehicle; when is 1, it means the i-th electric vehicle is discharging; when is 0, it means the i-th electric vehicle is charging.

[0147] The microgrid satisfies power balance, specifically as follows:

[0148] ;

[0149] ;

[0150] where, is the power generation of the thermal power unit of the microgrid at time t, is the charging and discharging power of the electric vehicle at time t, is the power loss of the microgrid at time t, is the load power of the microgrid at time t, I represents the number of electric vehicles dispatched by the microgrid within the statistical time interval, is the charging and discharging power of the i-th electric vehicle at time t.

[0151] Step 4. Based on the constraint conditions, solve the objective function involving multiple indicators of the microgrid to obtain the dispatching scheme of the electric vehicle.

[0152] Solve using an improved moth - flame optimization algorithm based on R - domination or multi - objective particle swarm optimization to obtain a scheduling scheme for electric vehicles, including the charging and discharging states and durations of the electric vehicles scheduled by the micro - grid within the statistical time interval.

[0153] Step Five: Schedule the charging and discharging of electric vehicles according to the scheduling scheme.

[0154] In this application example, the scheduling of the charging and discharging of electric vehicles is realized by establishing a mathematical model of the charging and discharging of electric vehicles, an objective function with the minimum carbon emissions and minimum fluctuations of the micro - grid, and the maximum resource benefit of electric vehicles, so as to reduce the carbon emissions of the micro - grid in the vehicle - grid interaction scenario, maintain the stability of the micro - grid, and at the same time increase the resource benefit of electric vehicles.

[0155] It should be understood that although the steps in the flowcharts involved in the above - mentioned embodiments are shown in sequence according to the arrows, these steps do not necessarily need to be executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above - mentioned embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily need to be executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0156] Based on the same inventive concept, the embodiment of the present application also provides a charging and discharging scheduling device for electric vehicles for implementing the charging and discharging scheduling method of electric vehicles involved above. The solution provided by this device to solve the problem is similar to the solution described in the above - mentioned method. Therefore, the specific limitations in one or more embodiments of the following charging and discharging scheduling devices for electric vehicles can refer to the limitations on the charging and discharging scheduling method of electric vehicles in the above text, and will not be repeated here.

[0157] In one embodiment, as Figure 4 shown, a charging and discharging scheduling device for electric vehicles is provided, including:

[0158] A first objective - function acquisition module 401, configured to obtain a first objective function with the minimum power volatility of the micro - grid as the goal based on the power change situation of the micro - grid at adjacent moments within the statistical time interval;

[0159] The second objective function module 402 is configured to obtain a second objective function aiming at minimizing the carbon emission of the microgrid based on the number of electric vehicles dispatched by the microgrid within a statistical time interval and the carbon emissions of charging and discharging of each electric vehicle at a single moment;

[0160] The third objective function module 403 is configured to obtain a third objective function aiming at maximizing the resource inflow of the electric vehicle based on the expression of the resource inflow obtained from selling electricity by the electric vehicle at a single moment, the expression of the resource cost generated by charging at a single moment, and the expression of the resource loss at a single moment;

[0161] The scheduling scheme acquisition module 404 is configured to obtain a scheduling scheme for the electric vehicle based on the first objective function, the second objective function, and the third objective function;

[0162] The scheduling processing module 405 is configured to schedule the charging and discharging of the electric vehicle according to the scheduling scheme.

[0163] In one embodiment, the device further includes a resource loss amount expression acquisition module, configured to:

[0164] Obtain the charging and discharging mathematical model of the electric vehicle; according to the charging and discharging mathematical model, obtain the expression of the state of charge of the electric vehicle battery at a single moment; according to the expression of the state of charge, obtain the expression of the resource loss amount.

[0165] In one embodiment, the third objective function module 403 is further configured to:

[0166] Subtract the expression of the resource cost generated by charging at a single moment and the expression of the resource loss at a single moment from the expression of the resource inflow obtained from selling electricity by the electric vehicle at a single moment, to obtain a third objective function aiming at maximizing the resource inflow of the electric vehicle.

[0167] In one embodiment, the scheduling scheme acquisition module 404 is further configured to:

[0168] Taking that the charging power of the electric vehicle battery at a single moment is not greater than the maximum charging power, the discharging power of the electric vehicle at a single moment is not greater than the maximum discharging power, and the state of charge of the electric vehicle battery at a single moment is within the upper and lower limit intervals as constraint conditions, solve the first objective function, the second objective function, and the third objective function; according to the solution result, obtain the scheduling scheme of the electric vehicle.

[0169] In one embodiment, the second objective function module 402 is further configured to:

[0170] Based on the power generation amount and carbon emission factor of the microgrid within the statistical time interval, an expression for the carbon emission amount related to the microgrid power generation is obtained; based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the carbon emission amount of each electric vehicle for charging and discharging at a single moment, an expression for the carbon emission amount related to the charging and discharging of electric vehicles is obtained; based on the expression for the carbon emission amount related to the microgrid power generation plus the expression for the carbon emission amount related to the charging and discharging of electric vehicles, a second objective function with the minimization of the carbon emission amount of the microgrid as the target is obtained.

[0171] In one embodiment, the second objective function module 402 is further configured to:

[0172] Based on the expression for the carbon emission amount related to the microgrid power generation minus the initial carbon quota of the microgrid and plus the expression for the carbon emission amount related to the charging and discharging of electric vehicles, a second objective function with the minimization of the carbon emission amount of the microgrid as the target is obtained.

[0173] Each module in the above-mentioned charging and discharging scheduling device of electric vehicles can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0174] In an exemplary embodiment, a computer device is provided, and its internal structure diagram can be as Figure 5 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through the system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the data involved in the above method. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a charging and discharging scheduling method for electric vehicles.

[0175] Those skilled in the art can understand, Figure 5The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0176] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps in the above-mentioned method embodiments are implemented.

[0177] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0178] In one embodiment, a computer program product is provided, on which a computer program is stored. The computer program is executed by a processor to implement the steps in the above-mentioned method embodiments.

[0179] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0180] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0181] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this application.

[0182] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for scheduling charging and discharging of an electric vehicle, characterized in that: The method comprises: Based on the power variation of the microgrid at adjacent moments within the statistical time interval, a first objective function with the goal of minimizing the power fluctuation rate of the microgrid is obtained; Based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the carbon emissions of each electric vehicle during charging and discharging at a single moment, a second objective function with the goal of minimizing the carbon emissions of the microgrid is obtained; Based on the expression of the resource inflow amount obtained by the electric vehicle due to electricity sales at a single moment, the expression of the resource consumption amount generated by charging at a single moment, and the expression of the resource loss amount at a single moment, a third objective function with the goal of maximizing the resource inflow amount of the electric vehicle is obtained; Based on the first objective function, the second objective function and the third objective function, a dispatching plan for electric vehicles is obtained; The charging and discharging of electric vehicles are scheduled according to the scheduling plan.

2. The method according to claim 1, characterized in that The method further comprises: Obtain the charging and discharging mathematical model of electric vehicles; According to the charging and discharging mathematical model, an expression for the battery charge of the electric vehicle at a single moment is obtained; According to the battery charge expression, the resource loss expression is obtained.

3. The method according to claim 1, characterized in that: Based on the expression of the resource inflow amount obtained by selling electricity at a single moment, the expression of the resource consumption amount generated by charging at a single moment, and the expression of the resource loss amount at a single moment, the third objective function with the goal of maximizing the resource inflow amount of the electric vehicle is obtained, including: The expression of the resource inflow amount obtained by selling electricity to electric vehicles at a single moment is subtracted from the expression of the resource consumption amount generated by charging at a single moment and the expression of the resource loss at a single moment, to obtain the third objective function with the goal of maximizing the resource inflow amount of electric vehicles.

4. The method according to claim 1, characterized in that: Based on the first objective function, the second objective function and the third objective function, a dispatching scheme for electric vehicles is obtained, including: Solving the first objective function, the second objective function and the third objective function with the constraint conditions that the charging power of the electric vehicle battery at a single moment is not greater than the maximum charging power, the discharging power of the electric vehicle at a single moment is not greater than the maximum discharging power, and the battery charge of the electric vehicle at a single moment is within the upper and lower limit intervals; According to the solution results, the dispatch plan of electric vehicles is obtained.

5. The method according to claim 1, characterized in that Based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the carbon emissions of each electric vehicle during charging and discharging at a single moment, the second objective function with the goal of minimizing the carbon emissions of the microgrid is obtained, including: Based on the power generation and carbon emission factor of the microgrid within the statistical time interval, the carbon emission expression related to the power generation of the microgrid is obtained; Based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the carbon emissions of each electric vehicle during charging and discharging at a single moment, the carbon emissions expression related to the charging and discharging of electric vehicles is obtained; Based on the carbon emission expression related to microgrid power generation and the carbon emission expression related to electric vehicle charging and discharging, a second objective function with the goal of minimizing the carbon emissions of the microgrid is obtained.

6. The method according to claim 5, characterized in that Based on the carbon emission expression related to microgrid power generation and the carbon emission expression related to electric vehicle charging and discharging, the second objective function with the goal of minimizing the carbon emission of the microgrid is obtained, including: Based on the carbon emission expression related to the power generation of the microgrid minus the initial carbon quota of the microgrid and adding the carbon emission expression related to the charging and discharging of electric vehicles, the second objective function with the goal of minimizing the carbon emissions of the microgrid is obtained.

7. A charging and discharging scheduling device for an electric vehicle, characterized in that: The device comprises: A first objective function acquisition module, used to obtain a first objective function with the goal of minimizing the power fluctuation rate of the microgrid based on the power variation of the microgrid at adjacent moments within the statistical time interval; A second objective function module is used to obtain a second objective function with the goal of minimizing the carbon emissions of the microgrid based on the number of electric vehicles dispatched by the microgrid within the statistical time interval and the charging and discharging carbon emissions of each electric vehicle at a single moment; A third objective function module, for obtaining a third objective function with the goal of maximizing the resource inflow of the electric vehicle based on an expression of the resource inflow amount obtained by selling electricity at a single moment, an expression of the resource consumption amount generated by charging at a single moment, and an expression of the resource loss amount at a single moment; A scheduling scheme acquisition module, used to obtain a scheduling scheme for electric vehicles based on the first objective function, the second objective function and the third objective function; The scheduling processing module is used to schedule the charging and discharging of the electric vehicle according to the scheduling plan.

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

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

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

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